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- Underwater Image Processing: State of the Art of Restoration and Image Enhancement Methods710
Some of the most recent methods that have been specifically developed for the underwater environment are reviewed, capable of extending the range of underwater imaging, improving image contrast and resolution.
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- Quantitative evaluation of color image segmentation results413
This paper considers the problem of the automatic evaluation of the results of color image segmentation, and identifies some limitations in this evaluation function, and proposes two enhanced functions that correspond more closely to visual judgment.
- On the use of deep learning for blind image quality assessment369
The best proposal, named DeepBIQ, estimates the image quality by average-pooling the scores predicted on multiple subregions of the original image, having a linear correlation coefficient with human subjective scores of almost 0.91.
- Image annotation using SVM314
An innovative image annotation tool for classifying image regions in one of seven classes - sky, skin, vegetation, snow, water, ground, and buildings - or as unknown is described.
- Content-based image retrieval289
The project IRIS1 (Image Retrieval for Information Systems) combines well-known methods and techniques in computer vision and AI in a new way to generate content descriptions of images in a textual form automatically.
- Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity285
A region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs) and self-similarity, which outperforms the state of the art.
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- 3D face detection using curvature analysis255
This work presents an innovative method that combines a feature-based approach with a holistic one for three-dimensional (3D) face detection, which has been tested, with good results, on some 150 3D faces acquired by a laser range scanner.
- Color constancy using CNNs232
Taking image patches as input, the CNN works in the spatial domain without using hand-crafted features that are employed by most previous methods to accurately predict the scene illumination.
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- An innovative algorithm for key frame extraction in video summarization185
The algorithm, which escapes the complexity of existing methods based, for example, on clustering or optimization strategies, dynamically and rapidly selects a variable number of key frames within each sequence by analyzing the differences between two consecutive frames of a video sequence.
- Color-based image retrieval using spatial-chromatic histograms176
A new indexing methodology for image databases integrating color and spatial information for content-based image retrieval, called Spatial-Chromatic Histogram (SCH), can be more satisfactory than standard techniques when the user would like to retrieve from the database the images that actually resemble the query image selected in their color distribution characteristics.
- Single and Multiple Illuminant Estimation Using Convolutional Neural Networks168
An extensive comparison with both local and global illuminant estimation methods in the state of the art, on standard data sets with single and multiple illuminants, proves the effectiveness of this three-stage method.
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- CNN-based features for retrieval and classification of food images145
Results demonstrate that the features extracted from the Food-475 database outperform the other ones showing that the authors need larger food databases in order to tackle the challenges in food recognition, and that the created database is a step forward toward this end.
- A segmentation algorithm for color images134
A method that combines clustering and region merging for color image segmentation using recursive one-dimensional histogram analysis and a criterion that takes into account color similarity and spatial proximity is presented.
- Deep learning for logo recognition126
The proposed recognition pipeline is composed of a logo region proposal followed by a Convolutional Neural Network specifically trained for logo classification, even if they are not precisely localized.
- A survey on methods for colour image indexing and retrieval in image databases126
This paper provides a comprehensive survey of the methods for color image indexing and retrieval described in the literature, in particular, image preprocessing, the features used to represent color information, and the measures adopted to compute the similarity between the features of two images are critically analyzed.
- Color balancing of digital photos using simple image statistics123
This paper describes a method for detecting and removing a color cast from a digital photo without any a priori knowledge of its semantic content, and proposes a modified version of the white balance algorithm for this purpose.
- How Far Can You Get by Combining Change Detection Algorithms?121
Results demonstrate that starting from simple algorithms the proposed IUTIS combination strategy can achieve comparable results with respect to more complex state-of-the-art change detection algorithms, while keeping the computational complexity affordable for real-time applications.
- Automatic color constancy algorithm selection and combination119
This work investigates how illuminant estimation techniques can be improved taking into account intrinsic, low level properties of the images, and shows how these properties can be used to drive the selection of the best algorithm for a given image.
- A relevance feedback mechanism for content-based image retrieval112
A new relevance feedback mechanism is described which evaluates the feature distributions of the images judged relevant, or not relevant, by the user and dynamically updates both the similarity measure and the query in order to accurately represent the user's particular information needs.
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- An interactive tool for manual, semi-automatic and automatic video annotation108
Results demonstrate that the use of the semi-automatic, as well as the automatic, modality drastically reduces the human effort while preserving the quality of the annotations.
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- Image registration by recognition of corresponding structures95
A method for automatic image registration which is characterized by its insensitivity to scaling, rotation, and intensity changes and an application to remote-sensing image alignment with a reference map is presented.
- Skin segmentation using multiple thresholding87
This study applies a genetic algorithm to determine the boundaries of the skin clusters in multiple color spaces, and trains the genetic algorithm and test the performance of the classifiers applying the GA suggested boundaries using the large and heterogeneous Compaq skin database.
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- Contrast image correction method75
The technique aims to correct images that simultaneously present overexposed and underexposed regions and to prevent halo artifacts, the bilateral filter is used as the mask of the exponential correction.
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- Evaluating color texture descriptors under large variations of controlled lighting conditions67
An extensive comparison of old and new texture features, with and without a color normalization step, is reported, with a particular focus on how these features are affected by small and large variations in the lighting conditions.
- Image Analysis and Processing – ICIAP 200967
This book constitutes the refereed proceedings of the 15th International Conference on Image Analysis and Processing, ICIAP 2009, held in Vietri sul Mare, Italy, in September 2009.
- Learning CNN-based Features for Retrieval of Food Images64
The Food524DB is built, the largest publicly available food dataset with 524 food classes and 247,636 images by merging food classes from existing datasets in the state of the art, and a Residual Network, ResNet-50, is fine tuned to be very effective for image recognition.
- A Novel Approach to Data Augmentation for Pavement Distress Segmentation63
It is shown how, starting from few labeled images, it is possible to augment small and long-tail datasets by producing new images with the associated semantic layouts and a remarkable increase in performance, especially with low cardinality classes, when CNNs are trained on the augmented datasets with respect to original datasets.
- Color image segmentation using Hopfield networks62
This paper presents two segmentation algorithms for color image segmentation based on Huang's idea of describing the segmentation problem as one of minimizing a suitable energy function for a Hopfield network.
- Automated Pruning for Deep Neural Network Compression60
This is the first study where the generalization capabilities in transfer learning tasks of the features extracted by a pruned network are analyzed, and it is shown that the representations learned using the proposed pruning methodology maintain the same effectiveness and generality of those learned by the corresponding non-compressed network on a set of different recognition tasks.
- Food Recognition and Leftover Estimation for Daily Diet Monitoring60
A system for automatic dietary monitoring of canteen customers based on robust computer vision techniques that recognizes foods and estimates food leftovers and results achieved on 1000 customers of a real canteen are promising.
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- Multitask painting categorization by deep multibranch neural network58
Among the different variants of the proposed network, the best method achieves accuracy levels of 56.5%, 57.2%, and 63.6% on the MultitaskPainting100k dataset for the tasks of artist, style and genre prediction respectively.
- No reference image quality classification for JPEG-distorted images56
This paper addresses the Image Quality Assessment of JPEG-distorted images by focusing on a classification problem that maps different objective metrics into different categorical quality classes, where No Reference metrics are considered as features, while the assigned classes come from psycho-visual experiments.
- IMAGE RETRIEVAL USING FUZZY EVALUATION OF COLOR SIMILARITY55
The paper describes the design and implementation of an information retrieval system using color as the index in its color image archive, and an example of its application is given, showing how the implemented system can be tailored to manage archives of images representing fabric samples.
- NTIRE 2024 Quality Assessment of AI-Generated Content Challenge54
This challenge is to address a major challenge in the field of image and video processing, namely, Image Quality Assessment (IQA) and Video Quality Assessment (VQA) for AI-Generated Content (AIGC).
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- Content-based similarity retrieval of trademarks using relevance feedback51
The hypothesis that the low-level image features used to index the trademark images can be correlated with image contents by applying a relevance feedback mechanism that evaluates the feature distributions of the images the user has judged relevant, or not relevant and dynamically updates both the similarity measure and query in order to better represent the user's particular information needs is investigated.
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- Logo Recognition Using CNN Features49
This paper proposes a method for logo recognition based on Convolutional Neural Networks, instead of the commonly used keypoint-based approaches, which involves the selection of candidate subwindows using an unsupervised segmentation algorithm and the SVM-based classification of such candidate regions using features computed by a CNN.
- Artistic photo filter removal using convolutional neural networks48
The method uses a convolutional neural network for the prediction of the coefficients of local polynomial transformations that are applied to the input image and shows that the quality of the restoration performed by the method is clearly superior to that of traditional color balancing and restoration procedures.
- Three-Dimensional Occlusion Detection and Restoration of Partially Occluded Faces48
This paper presents an innovative three dimensional occlusion detection and restoration strategy for the recognition of three dimensional faces partially occluded by unforeseen, extraneous objects and demonstrates the robustness and feasibility of the approach.
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- Combining local binary patterns and local color contrast for texture classification under varying illumination47
A texture descriptor for color texture classification specially designed to be robust against changes in the illumination conditions, which outperforms the original LBP approach and its color variants, even when these are computed after color normalization.
- Gappy PCA Classification for Occlusion Tolerant 3D Face Detection47
The proposed approach for the detection of faces in three dimensional scenes is tolerant against partial occlusions produced by the presence of any kind of object and can be used to improve the robustness of all those systems requiring a face detection stage in non-controlled scenarios.
- Quicklook2: An Integrated Multimedia System47
The design and integration with the relevance feedback mechanism of an indexing scheme based on triangle inequality to improve retrieval efficiency and the performance of the system is illustrated with examples from various application domains and for different types of queries.
- On the detection of pornographic digital images46
Both, decision forests of trees built according to CART (Classification And Regression Trees) methodology and Support Vectors Machines (SVM) have been used to perform the classification of pornographic and non-pornographic photographs.
- Benchmarking algorithms for food localization and semantic segmentation44
This paper conducts extensive experiments to evaluate ten state-of-the-art segmentation algorithms on two tasks: food localization and semantic food segmentation.
- Using a Relevance Feedback Mechanism to Improve Content-Based Image Retrieval44
A new relevance feedback mechanism is described that evaluates the distribution of the features of images judged relevant or not relevant by the user, and dynamically updates both the similarity measure and query in order to accurately represent the user's particular information needs.
- Video restoration based on deep learning: a comprehensive survey43
This paper provides a comprehensive review of the main features of existing video restoration methods based on deep learning, focusing on the main architectural components, strategies for motion handling, and loss functions.
- Color correction pipeline optimization for digital cameras43
Experimental results show that exploiting the cross-talks between the modules of the pipeline can lead to a higher color-rendition accuracy.
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- Local detectors and compact descriptors for visual search: A quantitative comparison42
This work extends the previous analysis using the MPEG CDVS Test Model framework to consider additional detectors and the use of color descriptors to achieve interoperability between different implementations of clients and servers.
- Fuzzy reasoning approach to similarity evaluation in image analysis42
A general strategy for similarity evaluation in image analysis considered as a cognitive process using fuzzy logic propositions to represent knowledge structures, and fuzzy reasoning to model inference mechanisms is proposed.
- Predicting Image Aesthetics with Deep Learning41
A canonical CNN architecture, originally trained to classify objects and scenes, is fine-tune by casting the image aesthetic prediction as a regression problem, which outperforms the best solution in the state of the art by almost 17 % in terms of Mean Residual Sum of Squares Error (MRSSE).
- Image orientation detection using LBP-based features and logistic regression41
An algorithm for the automatic detection of the image orientation that relies on the image content as described by Local Binary Patterns (LBP) is presented and its accuracy is comparable with that of human observers in detecting the correct orientation of a wide range of image contents.
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- Improving CNN-Based Texture Classification by Color Balancing40
It is shown how suitable color balancing models allow for a significant improvement in the accuracy in recognizing textures for many CNN architectures.
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- Color space transformations for digital photography exploiting information about the illuminant estimation process38
It is demonstrated that incorporating knowledge about the illuminant estimation behavior in the optimization of the color correction matrix makes it possible to alleviate the error amplification.
- Two new von Kries based chromatic adaptation transforms found by numerical optimization37
Experimental results report several statistics to prove the effectiveness of the proposed von Kries based chromatic adaptation transforms with respect to the state-of-the-art.
- An affordable multispectral imaging system for the digital museum37
It is shown that multispectral representations collected with such systems can be used for several purposes, including reproduction with current and future devices and support for monitoring and restoration, making them a natural choice for master copies in cultural institutions’ archives.
- AUTOMATIC CLASSIFICATION OF DIGITAL PHOTOGRAPHS BASED ON DECISION FORESTS37
It is shown here how low-level features can be related to semantic photo categories, such as indoor, outdoor and close-up, using decision forests consisting of trees constructed according to CART methodology.
- Browsing museum image collections on a multi-touch table35
A multi-touch tabletop system for browsing image databases, conceived for museums and art gallery exhibitions, that allows users to interactively create and manipulate image clusters where images are grouped according to their pictorial similarity.
- A method for the automatic indexing of colour images for effective image retrieval35
A new colour-based indexing method, integrating different approaches for describing colour information, can be more satisfactory than standard techniques in fields such as textiles, ceramics, and paintings when the user would like to retrieve from the database those images that actually resemble the query image selected in their colour distribution characteristics.
- Combining multiple features for color texture classification34
It is shown that the use of these descriptors in a multiple classifiers framework makes it possible to achieve a very high classification accuracy in classifying texture images acquired under different lighting conditions and how the proposed combining strategy hand-crafted and convolutional neural networks features can be used together to further improve the classification accuracy.
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- Semi-supervised cross-lingual speech emotion recognition33
A Semi-Supervised Learning (SSL) method for cross-lingual emotion recognition when only few labeled examples in the target domain are available, based on a Transformer, which adapts to the new domain by exploiting a pseudo-labeling strategy on the unlabeled utterances.
- Halfway through the semantic gap: Prosemantic features for image retrieval33
An image description approach based on prosemantic features, which are obtained through a two-level feature extraction process and used to index images in an image retrieval system where searches are performed using relevance feedback.
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- A hierarchical classification strategy for digital documents32
This work reports on the experience in the use of CART classifiers for the classification of images indexed by low-level perceptual features such as color, texture, and shape in compound documents.
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- Colorimetric calibration of color scanners by back-propagation31
A simple method for calibrating a color scanner employs a multilayer feed-forward neural network trained by back-propagation, using a standard color set as the training set.
- Unsupervised segmentation of hyperspectral remote sensing images with superpixels28
An unsupervised method that takes as input a preliminary hyperspectral superpixels segmentation together with the spectral pixel information and exploits the mean-shift clustering algorithm to demonstrate the validity of the proposed method in comparison with the state of the art.
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- Dynamic key-frame extraction for video summarization28
An innovative approach to the selection of representative frames of a video shot for video summarization that can dynamically, and rapidly select a variable number of key frame within each shot, does not exhibit the complexity of existing methods based on clustering algorithm strategies.
- A Smart Mirror for Emotion Monitoring in Home Environments27
This paper presents a general-purpose smart mirror that integrates several functionalities, standard and advanced, to support users in their everyday life and exploits a deep learning technique to develop most of the smart functionalities.
- Multimodal Car Driver Stress Recognition27
Experiments show that the best recognition results are obtained feeding the classifiers with the concatenation of the features of all the signals considered, reaching a micro average accuracy of 77.25% and 65.09% in the two experimental setups respectively.
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- Combining strategies for white balance27
This work considers six methods for automatic white balance available in the literature and considers a consensus decision that takes into account the compendium of the responses of all the considered algorithms.
- Computational Color Imaging 7th International Workshop, CCIW 2019, Chiba, Japan, March 27-29, 2019, Proceedings26
The Special Section on Computation Color Imaging is focused on color image processing, color image quality assessment, color vision modeling, and color image reproduction and several papers propose new descriptors for texture recognition or improvements to existing ones.
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- Computational Color Imaging: 4th International Workshop CCIW 201326
The Special Section on Computation Color Imaging is focused on color image processing, color image quality assessment, color vision modeling, and color image reproduction and several papers propose new descriptors for texture recognition or improvements to existing ones.
- Computational Color Imaging26
The Special Section on Computation Color Imaging is focused on color image processing, color image quality assessment, color vision modeling, and color image reproduction and several papers propose new descriptors for texture recognition or improvements to existing ones.
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- Deep Multibranch Neural Network for Painting Categorization25
To automatically predict painting’s artist and style, a novel deep multibranch neural network is proposed, where the different branches process the input image at different scales to jointly model the fine and coarse features of the painting.
- Remote Sensing Image Classification Exploiting Multiple Kernel Learning25
A novel procedure is presented that allows MKL to achieve good performance in the case of small training sets and experimental results on publicly available data sets demonstrate the feasibility of the proposed approach.
- Multicolored object recognition and location25
A novel computational strategy exploiting both shape and color information for the recognition and location of a two-dimensional model object on a known background is presented here.
- Spatial Sampling Network for Fast Scene Understanding23
This work presents three main novelties: a module named Improved Guided Upsampling Module that can replace in toto the decoder part in common semantic segmentation networks, and a new module based on spatial sampling to perform Instance Segmentation.
- Neural architecture search for image saliency fusion23
Extensive experimental evaluations show that the proposed saliency fusion approach outperforms the state-of-the-art on the MSRAB dataset and it is able to generalize to unseen data of different benchmark datasets.
- Image quality assessment by preprocessing and full reference model combination23
This paper investigates the hypothesis that combining error images with a visual attention model could allow a better fit of the psycho-visual data of the LIVE Image Quality assessment Database Release 2.0 and shows that the proposed quality assessment metric better correlates with the experimental data.
- Automatic Redeye Removal for Smart Enhancement of Photos of Unknown Origin23
A novel redeye removal algorithm is then applied automatically to the red eyes identified, and opportunely smoothed to avoid unnatural transitions between the corrected and original parts.
- Unsupervised Color Film Restoration Using Adaptive Color Equalization23
An innovative technique based on a model of human color perception, to correct color and dynamic range with no need of user supervision and with a very limited number of parameters is presented.
- Retinex preprocessing of uncalibrated images for color based image retrieval23
The performance of various color- based retrieval strategies is examined to see whether, and to what degree, the effectiveness of retrieval improves with Retinex-based preprocessing, regardless of the strategy adopted.
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- An Open-Source Platform for GIS Data Management and Analytics21
A software platform that facilitates the collection, visualization, management, and analysis of soil data, designed to handle data from various sources, including proximity, airborne, and spaceborne data, to enable precision agriculture.
- Robust smile detection using convolutional neural networks21
Experimental results show that the fully automated approach for smile detection outperforms state-of-the-art methods on both high- and low-quality images.
- Automatic selection of control-points from shadow structures†21
A procedure for the automatic selection of control-points in remote-sensing images of high-relief terrains for alignment with a reference map is described based on the recognition of shadow structures in the satellite image and on their comparison with the computer-generated shadows obtained from the Digital Terrain Model of the region.
- Full-Reference Image Quality Expression via Genetic Programming20
This work presents a framework for the formulation of SSIM-like image quality measures through genetic programming, explores different terminal sets, defined from the building blocks of structural similarity at different levels of abstraction, and proposes a two-stage genetic optimization that exploits hoist mutation to constrain the complexity of the solutions.
- Learning Parametric Functions for Color Image Enhancement20
A novel CNN-based method for image enhancement that simulates an expert retoucher that is fast and accurate at the same time thanks to the decoupling between the inference of the parameters and the color transformation.
- Image Analysis and Processing - ICIAP 201720
Results are promising and show that the rank aggregation methods can be used to improve the overall performance, reaching gains of more than 10% over state-of-the-art solutions.
- Cooking Action Recognition with iVAT: An Interactive Video Annotation Tool20
The iVAT interactive video annotation tool is developed to support manual, semi-automatic and automatic annotations obtained on the basis of the interaction of the user with various detection algorithms.
- Feature Extraction for Content-Based Image Retrieval20
An installation performance of the air conditioning apparatus in the instrument panel of the vehicle can be improved because of the shape of the heat exchanger.
- Semi-supervised anomaly detection for visual quality inspection19
A semi-supervised method that exploits a pre-trained Convolutional Neural Network autoencoder that is blended with a statistical-based transformation of the neural network embedding layer in order to remove anomalies from the input image.
- A Review of Redeye Detection and Removal in Digital Images Through Patents19
This paper summarizes the history and the state of the art of redeye detection and correction in digital photography, starting from the analysis of patents, and describes the main approaches with the help of flowcharts and figures.
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- An algorithm for the selection of high-contrast color sets19
The color-coding problem is formulated here as a combinatorial optimization problem on graphs and an algorithm is presented that performs well and does not require that the function used to code the similarity between colors be a distance function.
- Evaluating CNN-Based Semantic Food Segmentation Across Illuminants18
Evaluating the performance of an efficient DCNN with respect to variability in illumination conditions that can be found in food images taken in real scenarios and evaluating the food vs. non-food segmentation performance of the network in terms of standard Intersection over Union (IoU) measure.
- Local Angular Patterns for Color Texture Classification18
A new color texture descriptor, specially designed to be robust to changes in the color of the illuminant, is defined, that is called Local Angular Patterns, which outperforms the state-of-the-art on a dataset of food textures.
- Color Coding for Data Visualization18
How a color scale should be designed to effectively represent both qualitative and quantitative information is discussed to critically discuss.
- Illuminant Invariant Descriptors for Color Texture Classification17
A novel descriptor for color texture analysis specially designed to deal with changes in illumination in imaging is presented, based on a combination of the LBP approach with a measure of color contrast defined as the angle between two color vectors in an orthonormal color space.
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- Quasi Real-Time Apple Defect Segmentation Using Deep Learning16
This paper proposes a deep learning approach for the automated segmentation of apple defects using convolutional neural networks based on a U-shaped architecture with skip-connections only within the noise reduction block, and shows that the proposal outperforms in terms of segmentation accuracy general-purpose deep learning architectures commonly used for segmentation tasks.
- An Efficient Method for No-Reference Video Quality Assessment16
The results show that the proposed method at a substantially lower computational cost predicts subjective video quality in line with the state of the art methods on individual databases and generalizes better than existing methods in cross-database setup.
- An analysis of spectral similarity measures16
This paper divides the most used measures for the assessment of spectral similarity of reflectance and radiance signals into five groups on the basis of the type of errors they measure and analyzes the behaviour of the selected metrics with respect to two different color properties.
- No-Reference Quality Assessment of In-Capture Distorted Videos16
A no-reference method for the assessment of the quality of videos affected by in-capture distortions due to camera hardware and processing software is introduced and its ability to generalize in cross-database setup is demonstrated.
- ARC: Angle-Retaining Chromaticity diagram for color constancy error analysis16
This work proposes an Angle-Retaining Chromaticity diagram (ARC) for the visual analysis of the estimated illuminants and the corresponding errors, and provides both quantitative and qualitative proof of the superiority of ARC in preserving angular distances compared to other chromaticity diagrams.
- Intensity and color descriptors for texture classification16
This paper presents a descriptor for texture classification based on the histogram of a local measure of the color contrast that shows a performance improvement with respect to results achieved by baseline methods thus demonstrating the effectiveness of the proposed texture features.
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- Smart Photo Sticking16
The proposed approach improves previous solutions both considering a self-adaptive image cropping algorithm, exploiting visual and semantic information, and introducing an optimization process based on a genetic algorithm.
- Dynamic storyboards for video content summarization16
This work proposes an innovative, general purpose, approach to the selection and hierarchical representation of key frames of a video sequence for video summarization.
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- T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods15
A very large, heterogeneous database of high-quality texture images acquired under variable conditions, T1K+ contains 1129 classes of textures, which allows the design of experiments especially aimed at understanding the specific issues related to texture classification and retrieval.
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- Learning Illuminant Estimation from Object Recognition14
This is the first example of a deep learning architecture for illuminant estimation that is trained without ground truth illuminants, and it is shown to outperform most deep learning methods in a cross-dataset evaluation setup, and to present competitive results in a comparison with parametric solutions.
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- Noisy images-JPEG compressed: subjective and objective image quality evaluation14
The aim of this work is to study image quality of both single and multiply distorted images and how subjective data correlate with No Reference state-of-the-art quality metrics.
- How to assess image quality within a workflow chain: an overview14
An overview of the state of the art of the IQA methods is provided, putting in evidence their applicability and limitations in different application domains, and general guidelines for three workflow chains in which IQA policies are required are presented.
- Erratum to: An innovative algorithm for key frame extraction in video summarization14
This work proposes an innovative approach to the selection of representative (key) frames of a video sequence for video summarization, which escapes the complexity of existing methods based on clustering or optimization strategies and can extract the key frames on the fly.
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- Knowledge-based contextual recognition and sieving of digital images14
A sieve is realized as a conditional attributed Lindenmayer-system with interaction, a generative tool defined in the paper.
- General Purpose Optimization Library (GPOL): A Flexible and Efficient Multi-Purpose Optimization Library in Python13
The General Purpose Optimization Library (GPOL) is proposed, a flexible and efficient multipurpose optimization library that covers a wide range of stochastic iterative search algorithms, through which flexible and modular implementation can allow for solving many different problem types from the fields of continuous and combinatorial optimization and supervised machine learning problem solving.
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- A computational strategy exploiting genetic algorithms to recover color surface reflectance functions13
This work addresses the recovery of a surface reflectance function, given the tristimulus values under one or more illuminants, using a variety of standard datasets.
- A modular procedure for automatic red eye correction in digital photos13
An algorithm for the automatic removal of "redeye" from digital photos is described, first an adaptive color cast removal algorithm is applied to correct the color photo, and the redeye removal algorithms are applied automatically to the red eyes identified.
- Color set selection for nominal coding by Hopfield networks13
The specification of high contrast color sets is a fundamental step towards the optimal use of color to represent qualitative data, and a Hopfield neural network of analog neurons is designed to find approximate solutions.
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- Fine-Grained Face Annotation Using Deep Multi-Task CNN12
A multi-task learning-based convolutional neural network (MTL-CNN) able to estimate multiple tags describing face images simultaneously and taking into account the correlation among face attributes is presented.
- Multiscale fully convolutional network for image saliency12
Despite training the model on binary ground truths only, the method is able to output a continuous-valued confidence map, which represents the probability of each image pixel being salient, which proves to be very effective in a comparison with the state-of-the-art.
- On the use of supervised features for unsupervised image categorization: An evaluation12
It is demonstrated that supervised features can be effectively used also for unsupervised image categorization, that is, for grouping semantically similar images.
- Prosemantic Features for Content-Based Image Retrieval12
An image description approach based on prosemantic features that allows for a more successful and quick retrieval of the query images and to verify the effectiveness of the approach, a target search experiment is designed.
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- A unifying representation for pixel-precise distance estimation11
Using the proposed representation, datasets acquired with different devices can be effortlessly combined to build more powerful models, and monocular distance estimation can be performed on images acquired from devices that were never used during training.
- On Comparing Color Spaces for Food Segmentation11
Investigation of a number of color encoding schemes and color spaces for food segmentation exploiting the JSEG algorithm finds that significant improvements in segmentation can be achieved with a proper color space selection and by learning the proper setting of the segmentation parameters from a training set.
- Feature Extraction for Content-Based Image Retrieval11
This study has shown that the wavelet descriptors provide the most effective features in content-based retrieval and proposes a new method for finding a starting point for this feature.
- Training Set Selection for Multispectral Imaging Systems Characterization11
Three novel approaches in selecting a training set to be used for the characterization of a multispectral acquisition system are proposed and the performances of the Linear Distance Maximization Method make it the best choice among all the methods tried for application in a general context.
- Training set selection for multispectral imaging system Characterisation11
Three novel approaches in selecting a training set to be used for the characterization of a multispectral acquisition system are proposed and the performances of the Linear Distance Maximization Method make it the best choice among all the methods tried for application in a general context.
- DALib: A Curated Repository of Libraries for Data Augmentation in Computer Vision10
This paper focuses on the exploration of the most widely adopted libraries specifically designed for data augmentation in computer vision tasks, and presents an organized classification of the different approaches employed by these libraries, along with accompanying application examples.
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- Aesthetics Assessment of Images Containing Faces10
This paper exploits three different Convolutional Neural Networks to encode information regarding perceptual quality, global image aesthetics, and facial attributes; then, a model is trained to combine these features to explicitly predict the aesthetics of images containing faces.
- Computational Color Imaging10
The present paper discusses the concept of subtractive color mixing widely used in color hardcopy applications and shows that a more realistic concept would be “spectral mixing”: the physical description of the coloration of light by printed surfaces comes from the mixing of light components selectively absorbed by inks or dyes during their patch within the printing materials.
- Error-Tolerant Color Rendering for Digital Cameras10
This work designs extended color correction pipelines which exploit the crosstalks between their modules to lead to a higher color rendition accuracy.
- Intangible Heritage Management and Multimodal Navigation10
This chapter presents tools and methods which have been developed in order to manage and consult multimedia ethnographic archives for texts, images, audios (both music and speech), and videos.
- Content Aware Image Enhancement10
The overall quality of images is improved by a modular procedure automatically driven by the image class and content by integrating imaging and vision for content-aware enhancement and processing of digital photographs.
- Image Annotation for Adaptive Enhancement of Uncalibrated Color Images10
An innovative image annotation tool, based on a multi-class Support Vector Machine, for classifying image pixels in one of seven classes – sky, skin, vegetation, snow, water, ground, and man-made structures – or as unknown, is described.
- Color for Image Indexing and Retrieval10
This special issue is aimed at the dissemination of contributions in the area of color utilization in the exploration and visualization of image data repositories for the purpose of content-based image access, and how to combine color, shape, and texture information into a unified framework.
- Selection of filters for multispectral acquisition using the filter vectors analysis method10
The Filter Vectors Analysis Method method is introduced, a statistical analysis of the data resulting from an acquisition of a representive target, and tries to identify those filters that yield the most information in the given environmental conditions.
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- Learning color-appearance models by means of feed-forward neural networks10
Experimental evidence is presented that in several “standard” viewing conditions recommended for testing color-appearance models, the same network architecture is capable of learning quite satisfactorily the transformations performed by different color-Appearance models.
- RGB color constancy using multispectral pixel information9
A method that exploits multispectral imaging for illuminant estimation, and then applies illuminant correction in the raw RGB domain to achieve computational color constancy is proposed.
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- Training Efficient Semantic Segmentation CNNs on Multiple Datasets9
This work investigates a simple approach to modify semantic segmentation CNNs in order to train them on multiple datasets with heterogeneous groundtruths, and shows that the networks are trainable with the implemented method even though it highlights the limit of current efficient architectures when dealing withheterogeneous and large datasets.
- A semi-automatic annotation tool for cooking video9
This work presents an interactive, semi-automatic tool for the annotation of cooking videos that integrates computer vision techniques under the supervision of the user and the accuracy is increased, the human effort is reduced and the performance and usability are evaluated.
- Color transfer using semantic image annotation9
An automatic local color transfer method based on semantic image annotation that permits to automatically transfer the color distribution from regions of the source and target images annotated with the same class (for example the class "sky").
- A recall or precision oriented skin classifier using binary combining strategies9
It is shown that the performance of explicit skin cluster classifiers can be enhanced by preprocessing the images with a white balance algorithm, and different combining strategies are applied to these binary classifiers to further improve their performance in terms of recall and/or precision.
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- Deriving Spectral, Reflectance Functions of Computer‐Simulated Object Colours9
A method is presented which, given the RGB values of a colour stimulus displayed on a given cathode ray tube, makes it possible to find a spectral reflectance function characterizing an object colour.
- Modeling image aesthetics through aesthetics-related attributes8
A method that learns the aesthetics score on the basis of the prediction of aesthetics-related attributes and outperforms the state of the art of about 5.5% in terms of Spearman’s Rankorder Correlation Coefficient.
- A Genetic Algorithm to Combine Deep Features for the Aesthetic Assessment of Images Containing Faces8
Experimental results show that the approach outperforms existing methods for both binary, i.e., low/high, and continuous aesthetic score prediction on four different image databases in the state-of-the-art.
- No Reference, Opinion Unaware Image Quality Assessment by Anomaly Detection8
An anomaly detection based image quality assessment method which exploits the correlations between feature maps from a pre-trained Convolutional Neural Network to estimate the quality score combining the average of the correlation and the output from an anomaly detection method.
- Consensus-driven illuminant estimation with GANs8
A method is presented that exploits a generative adversarial network architecture to generate a spatially-varying illuminant map, which is then transformed by consensus into a global illuminants estimation, in the form of a single RGB triplet.
- Evaluation of Automatic Image Color Theme Extraction Methods8
Results show the best color theme is extracted by using a supervised method based on a regression model trained on user-defined color themes and that the computational metric adopted is comparable to a subjective one.
- Turning a Digital Camera into an Absolute 2D Tele‐Colorimeter8
A simple and effective technique for absolute colorimetric camera characterization, invariant to changes in exposure/aperture and scene irradiance, suitable in a wide range of applications including image‐based reflectance measurements, spectral pre‐filtering and spectral upsampling for rendering, to improve colour accuracy in high dynamic range imaging.
- On the Robustness of Color Texture Descriptors across Illuminants8
This paper recovered the spectral reflectances of 1360 texture images from the Outex 13 data set and rendered them as if they were taken under 33 different illuminants, measuring the classification performance of the texture features considered.
- Computational Strategies for Skin Detection8
A high-level computational strategy, which uses a face detector in the pre-processing step, and two different implementations of it are proposed: one relies on an adaptive single gaussian model, the other a fixed threshold skin cluster detector on an illuminant-independent image representation.
- Classification-Based Color Constancy8
This work has designed a strategy for the selection of the most appropriate algorithm on the basis of the classification results, and tested it on a subset of the widely used Funt and Ciurea dataset.
- Pixel based skin colour classification exploiting explicit skin cluster definition methods8
The performance, on a large and heterogeneous image database, of various skin detectors based on explicit colour skin cluster definition, coupled with a cast remover to see whether, and to what degree, the effectiveness of classification is improved, regardless of the strategy adopted.
- Innovative method for spectral-based printer characterization8
To improve the performance of the direct Neugebauer model in computing the reflectance spectrum of the print, given the amounts of ink, a method that exploits the results of the numerical inversion of the NeugeBauer model to estimate a correction of the amount of black ink computed on RGB values is designed.
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- Content-based image classification.8
This work addresses the problem of distinguishing photographs from graphics and texts purely on the basis of low-level feature analysis and reports the preliminary results of the experimentation.
- A GENERAL-PURPOSE PROCEDURE FOR COMPLEX GRAPHIC SYMBOL RECOGNITION8
A general-purpose procedure for the recognition of graphic symbols in line-drawing images is presented here and it is suggested that a noise-free symbol database is available and that both the model symbols and the processed image have been broken down into elementary structures.
- Computer Aided Color Coding8
A color coding system based on the fundamental principles of human vision that allows users to generate unordered or ordered color sets for data representation on both screen and paper in a simple and intuitive way.
- Color specification by visual interaction8
A visual language for communicating colors by appearance between the user and the computer system is presented, making possible both coarse and fine specification of color specification in an increasing number of computer-graphics applications.
- Blind quality assessment of authentically distorted images7
This article presents a convolutional neural network based BIQA model that encodes the input image into multi-level features to estimate the perceptual quality score and shows that the proposed method achieves comparable results with state-of-the-art methods in intra-dataset experiments and is more effective in cross-datASet experiments.
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- CNN-Based Refactoring of Hand-Designed Filters for Texture Analysis: A Classic Revisited7
This work proposes the use of convolutional networks for refactoring traditional, hand-designed filters, and shows that the refactored filters can be conveniently used ‘off-the-shelf’ to achieve better performance than obtained with the original filters, but at the same computational cost.
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- Grouping strategies to improve the correlation between subjective and objective image quality data7
This paper presents relevant background, along with the first attempts to derive experimentally and further model the VPF and CSFs, and examines the contrast detection and discrimination frameworks developed by Barten.
- Image orientation detection using low-level features and faces7
This work proposes a system which automatically detects the correct orientation of digital photographs, which exploits the information provided by a face detector and a set of low-level features related to distributions in the image of color and edges.
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- Image retrieval using dynamic spatial chromatic histograms7
An innovative image retrieval strategy is introduced, the Dynamic Spatial Chromatic Histogram, which makes it possible to take into account spatial information in a flexible way without greatly adding to computation costs.
- Content-Based Classification of Digital Photos7
It is shown that it is possible to relate low-level visual features to semantic photo categories, such as indoor, outdoor and close-up, using tree classifiers.
- Multimedia search engine with relevance feedback7
A web-based protytpe for the interactive search of items in quality electronic catalogues based on a multimedia information retrieval architecture that allows the user to query a multimedia database according to several retrieval strategies, and progressively refine the system's response by indicating the relevance, or non-relevance of the items retrieved.
- Improving RGB illuminant estimation exploiting spectral average radiance6
A method that enhances RGB color constancy accuracy by combining neural network and k-means clustering techniques and the combination of the illuminant estimation in the RGB color and in the spectral domains, as a strategy to provide a refined estimation in the RGB color domain.
- On the Use of Visual Transformer for Image Complexity Assessment6
This paper explores the use of recent deep-learning approaches based on Visual Transformer to extract robust information for image complexity estimation in a transfer learning paradigm, and proposes to leverage three visual backbones, CLIP, DINO-v2, and ImageNetViT, as feature extractors, coupled with a Support Vector Regressor with Radial Basis Function kernel as an image complexity estimator.
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- Genetic programming for structural similarity design at multiple spatial scales6
A comprehensive analysis of the feature selection indicates that, for extracting multi-scale similarities, spatially-varying convolutions are more effective than dilated convolutions, and there is evidence that the IQAMs learned for one database can be successfully transferred to previously unseen databases.
- Analyzing color harmony of food images6
A computational pipeline that includes color segmentation, color palette extraction and color harmony prediction makes it possible to analyze the emotions elicited by pairs and multiple combinations of food dishes.
- Image Memorability Using Diverse Visual Features and Soft Attention6
The proposed solution exploits feature maps extracted from two Convolutional Neural Networks pre-trained for object recognition and memorability estimation respectively that are enhanced using a soft attention mechanism in order to let the model focus on highly informative image regions for memorable estimation.
- Artistic Photo Filtering Recognition Using CNNs6
This paper proposes an approach based on deep Convolutional Neural Networks to recognize artistic photo filters applied to images, and shows that not only it is possible to reliably determine whether or not one of these filters has been applied, but also which one.
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- Toward a Unified Model for Information Quality6
A model which allows to define in an uniform way information quality dimensions related to heterogeneous types of information, such as structured data managed in data bases, semi-structured and unstructured texts and images, and a first attempt to unify the information quality issue for heterogeneous information types is presented.
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- Reflectance functions estimation from tri-stimulus values6
This work addresses the problem of synthesizing a spectral reflectance function, given the standard CIE 1931 tristimulus values, by proposing a linear combination of a small number of basis functions.
- Reflectance function estimation from tristimulus values6
This work addresses the problem of synthesizing a spectral reflectance function, given the standard CIE 1931 tristimulus values, by proposing a linear combination of a small number of basis functions.
- Tunable cast remover for digital photographs6
An adaptive and tunable color cast removal algorithm that has been tuned and tested, with positive results, on a large data set of images downloaded from personal web-pages, or acquired by various digital cameras.
- Spectral-Based Printer Characterization6
A separation procedure based on the inversion of the Yule-Nielsen modified Spectral Neugebauer model is designed and a method that exploits the results of its numerical inversion to estimate a correction of the amount of black ink computed on RGB values is designed.
- Innovative algorithm for cast detection6
The paper describes a method for detecting a color cast in a digital image without any a priori knowledge of its semantic content, and has been tuned and successfully tested on a large data set of images.
- A system for the automatic selection of conspicuous color sets for qualitative data display6
The authors describe the main features of a system supporting the selection of color palettes for qualitative data representation, such as in supervised or unsupervised image classification, based on visual interaction.
- Faithful cross-media color matching using neural networks6
A practical approach to accurate color rendering is proposed, integrating colorimetric and interactive methods by means of feed-forward neural networks trained by back-propagation, offering accurate color matching with a minimum of low cost equipment and little effort on the part of the user.
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- Deep Multi-Stage Approach For Emotional Body Gesture Recognition In Job Interview5
This work proposes a deep multi-stage architecture that is able to deal with two tasks of pose estimation and emotion classification for emotional body gesture recognition and proposes a representation technique based on the superposition of skeletons to generate a single image synthesizing the different poses of the subject.
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- Emerging Methods for Color Image and Video Quality Enhancement5
This paper aims to demonstrate the efforts towards in-situ applicability of EMMARM, as to provide real-time information about the response of the immune system to EMTs.
- Region-Based Illuminant Estimation for Effective Color Correction5
A region-based color constancy algorithm able to automatically select (and/or blend) among different color corrections, including a conservative do nothing strategy.
- Hierarchical browsing of video key frames5
An innovative, general purpose, method to the selection and hierarchical representation of key frames of a video sequence for video summarization is proposed, able to create a hierarchical storyboard that the user may easily browse.
- Multidomain pixel analysis for illuminant estimation and compensation5
An algorithm, not dependent on the acquiring device, for illuminant estimation and compensation directly in the color filter array (CFA) domain of digital still cameras, which takes into account both chromaticity and intensity information of the image data, and performs the illuminants compensation by a diagonal transform.
- Training Set and Filters Selection for the Efficient Use of Multispectral Acquisition Systems5
This paper assesses the performance of the evaluated methods for training set and filter selection on the results of a typical multispectral acquisition system, and compares the corresponding estimates for the reflectances of a representative target to the values measured using a spectrophotometer.
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- Color Based Image Retrieval of Uncalibrated Images5
The performance of various color-based retrieval strategies when coupled with Retinex-based pre-processing is examined to see whether, and to what degree, the effectiveness of retrieval is improved, regardless of the strategy adopted.
- Indexing Color-Texture Image Patterns5
Experimental results on a database of images of random color textures confirm the feasibility of this method for indexing complex color texture images, which outperforms more standard procedures in retrieval accuracy and at lower computational costs.
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- A fuzzy knowledge-based system for biomedical image interpretation5
A general purpose knowledge-based system for biomedical image interpretation that acquires knowledge directly from the experts by means of a user friendly dialogue and tailors the system to a particular biomedical application is presented.
- Towards the integration of remote sensing images within a cartographic system5
Current research aims to reduce or eliminate manual intervention both in the selection of control points for image registration and in the conversion of image structures into cartography-relevant vector elements.
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- Parameters optimization of the Structural Similarity Index4
It is experimentally observed that better results can be obtained by penalizing the overall similarity only for very low levels of luminance similarity, and a comparison of SSIM with the optimized parameters against other metrics for full reference quality assessment, showing superior performance on a different dataset.
- Autocropping: A Closer Look at Benchmark Datasets4
A detailed analysis of the main datasets in the state of the art in terms of statistics, diversity and coverage of the selected sub-regions, namely the ground-truth candidate views shows that each dataset models the cropping problem differently.
- Unsupervised color coding for visualizing image classification results4
A general purpose system that, given as input a segmented/classified image, automatically provides different visual outputs exploiting solid colors, color boundaries, and transparent colors and places a textual label in the less salient sub-region of the corresponding class if the names of the classes are given.
- Quality of Images4
An image is the result of the optical imaging process which maps physical scene properties onto a two-dimensional luminance distribution; it encodes important and useful information about the geometry of the scene and the properties of the objects located within this scene.
- Scoring recognizability of faces for security applications4
The system implements features filtering scheme combined with a skin-based face detection to improve its the robustness to false positives and cartoon-like faces and takes into account the recognizability trend over a customizable sliding time window to allow a high level analysis of the subject behaviour.
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- Prosemantic Image Retrieval4
The system effectiveness will be proved for both category and target search on two standard image databases, even without a "good" initial example and ancillary information, such as device metadata, text annotations, etc.
- Image quality: a tool for no-reference assessment methods4
An image quality assessment tool composed of different modules that implement several No Reference (NR) metrics that aims to give a structured view of a collection of objective metrics that are available for the different distortions within an integrated framework.
- Multiple image thumbnailing4
A new self-adaptive image cropping algorithm that is able to detect several relevant regions in the image and can then be sequentially proposed as thumbnails, to the user according to their relevance order, thus allowing the viewer to visualize the relevant image content and eventually to display or print only those regions in which he is more interested in.
- Semantic classification, low level features and relevance feedback for content-based image retrieval4
The qualitative experiments performed on a database of more than 46,000 photos downloaded from the Web show that the combination of semantic and low level features coupled with a relevance feedback algorithm, effectively improve the accuracy of the image retrieval sessions.
- An Evolutionary Framework for Colorimetric Characterization of Scanners4
This work presents an evolutionary framework for colorimetric characterization of scanners that uses genetic programming for assessing a characterizing polynomial and genetic algorithms to assess suitable coefficients of that polynometric.
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- Modeling Dot Gain and Inks Interaction4
A novel strategy to describe dot gain and interaction among inks in the definition of a printer model employing the Yule Nielsen Spectral Neugebauer equation is presented and may be extended to be used for characterizing devices having more than four inks.
- Acquisition and Mosaicking of Large / High-Resolution Multi- / Hyper-Spectral Images4
This paper briefly introduces the theoretical framework of multispectral imaging, particularly with regard to 'wide-band' mult ispectral acquisition, and drops any distinction between hyper- and multispecting, and only uses the latter term.
- An Empirical Approach for Spectral Color Printers Characterization4
This work treats inkjet printers as RGB devices, and exploits finite-dimensional linear models to reduce the amount of information required to characterize them, and compares the behavior of 15 different networks to compute reflectance spectra from RGB digital counts.
- Gamut boundary determination for a color printer using the Face Triangulation Method4
A new method to estimate the physical gamut boundary of a colour printer using the Face Triangulation Method, which has been tested on a real device, using two different paper media, and a common type of Gamut Boundary Descriptor.
- Selection of Training sets for the characterisation of multispectral imaging systems4
Two novel approaches in selecting a training set to be used for the characterisation of a multispectral acquisition system are proposed and it is proposed that the selected training sets will have low numerosity and broad applicability.
- Semantic labeling of digital photos by classification4
This paper addresses the problem of annotating photographs with broad semantic labels by designing a hierarchical classification strategy which first classifies images as pornographic or not-pornographic, and then classification as indoor, outdoor, or close-up.
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- Quicklook 2 : an integrated multimedia system with learning capabilities4
The main features of Quicklook are described, a system that combines in a single framework the alphanumeric relational query, the content-based image query exploiting automatically computed low-level image features, and the textural similarity query exploiting any textual attached to image database items.
- New classification strategy for color documents4
A hierarchical classification for photographs, graphics, texts and compound documents is described using the use of Cart trees for classification and the indexing of the images considering only low-level perceptual features, such as color, texture, and shape, automatically computed on the images.
- System for the automatic selection of conspicuous color sets for qualitative data display and visual interface design4
The main feature of a system supporting the selection of color palettes for qualitative data representation and graphic interface design based on visual interaction providing effective tools for browsing the Munsell color space and setting perceptual constraints on the number and type of colors the system selects automatically.
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- Semantic segmentation network stacking with genetic programming3
This paper explores genetic programming (GP) as a meta-model that combines four different efficiency-oriented networks for the analysis of urban scenes to develop efficient and accurate combination models that could be easily interpreted, therefore allowing gathering some hints on how to improve the existing networks.
- Shallow camera pipeline for night photography rendering3
A camera pipeline for rendering visually pleasing photographs in low light conditions, characterized by a shallow structure and by a low parameter count, is introduced, which reached the fifth place in the NTIRE2022 Night Photography Rendering challenge.
- Analyzing and Recognizing Food in Constrained and Unconstrained Environments3
The main solutions developed and results achieved for food localization, segmentation, recognition and analysis based on Computer Vision developed at the Imaging and Vision Laboratory in the last 12 years are presented.
- CNN-based image quality assessment of consumer photographs3
This article schematically illustrates how CNN-based framework for evaluating image quality of consumer photographs is made up of several building blocks that can be implemented in different ways and combined to create feasible solutions that take the most positive characteristics of CNNs while mitigating their intrinsic limitations.
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- Absolute colorimetric characterization of a DSLR camera3
A simple but effective technique for absolute colorimetric camera characterization that offers a large dynamic range requiring just a single, off-the-shelf target and a commonly available controllable light source for the characterization.
- Face-Based Illuminant Estimation3
This work uses a face detector to find faces in the scene, and the corresponding skin colors to estimate the chromaticity of the illuminant, based on two observations: first, skin colors tend to form a cluster in the color space, making it a cue to estimates the Illuminant in thescene.
- A no-reference metric for demosaicing artifacts that fits psycho-visual experiments3
The present work concerns the analysis of how demosaicing artifacts affect image quality and proposes a novel no-reference metric based on measures of blurriness, chromatic and achromatic distortions to fit the psycho-visual data.
- A sharpness measure on automatically selected edge segments3
This work presents an automatic method that selects edge segments, making it possible to evaluate sharpness on more reliable data, and proposes a new sharpness metric for natural images.
- Genetic Algorithms for Training Data and Polynomial Optimization in Colorimetric Characterization of Scanners3
A framework based on Genetic Algorithms to select training samples from large datasets and has the ability to optimize the training samples and the characterizing polynomial’s coefficients at the same time.
- No-reference metrics for demosaicing3
This work proposes an algorithm to identify patterns and measure their visibility in order to estimate the perceived quality of rendered images and determines the relationships between subjective scores and the proposed measure to obtain a reliable no-reference metric.
- Spectral-based printer modeling and characterization3
An innovative analytical printer model based on the Yule-Nielsen Spectral Neugebauer equation is described and for- mulated with a large number of degrees of freedom in order to ac- count for dot-gain, ink interactions, and printer driver operations.
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- Leveraging foundation model DINO-v2 for image complexity estimation2
This is the first work that leverage and evaluate different features extracted from a foundation model for image complexity estimation, and it is demonstrated that the general-purpose features of DINO-v2 can be effectively used for complexity estimation.
- Synthetic Data Pretraining for Hyperspectral Image Super-Resolution2
This paper addresses the challenge of data scarcity in the development of methods for spatial super-resolution of hyperspectral images (HSI-SR) by leveraging advances in spectral reconstruction methods to create a vast dataset with high spatial resolution and plausible spectra from RGB images, to be used for pretraining HSI-SR methods.
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- A health telemonitoring platform based on data integration from different sources2
The implemented telemonitoring platform is designed to process the acquired data using machine learning algorithms, and to provide patients and physicians the physiological health parameters with a user-friendly, comprehensive, and easy to understand dashboard which monitors the parameters through time.
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- CNN-based Rain Reduction in Street View Images2
Experimental results show that the Convolutional Neural Network model presented is able to outperform the state of the art in terms of two commonly used image quality metrics, and that it is capable to improve the performances of an OCR model to detect and recognise text in the wild.
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- A Fully Convolutional Network for Salient Object Detection2
A solution is proposed that exploits intermediate activations of a Fully Convolutional Neural Network previously trained for the recognition of 1,000 object classes, in order to gather generic object information at different levels of resolution by using both convolution and convolution-transpose layers.
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- Modeling Image Quality2
This contribution aims to provide an overview of the state of the art of the Image Quality Assessment (IQA) methods reviewing the literature on objective image quality assessment, and classifying and summarizing the available metrics.
- Object detection using feature-based template matching2
This work presents a fast technique for template matching, able to use histogram-based similarity measures on complex descriptors, and focuses on Color Histograms (CH), Histograms of Oriented Gradients (HOG), and Bag of visual Words histograms (BOW).
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- Occlusions in Face Recognition: a 3D Approach2
A method for removing glasses from a frontal image of the human face using a cascade of classifiers trained to detect subparts of the face and a method using local approaches which divide the face into parts which are independently compared.
- No-reference metrics for JPEG: analysis and refinement using wavelets2
Experimental results show that information about the visual content of the image can be exploited to improve the estimation of the quality of JPEG compressed images.
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- Image quality assessment in multimedia applications2
An organized overview of image quality assessment methods by putting in evidence their applicability and limitations in different application domains is provided.
- Automatic color patch selection for painting identification2
A new method to define a digital signature of a painting composed by a set of patches that are automatically selected as the images regions containing the most relevant information, and the experimental results are presented.
- INTEGRATING IMAGING AND VISION FOR CONTENT-SPECIFIC IMAGE ENHANCEMENT2
The overall quality of digital photographs is improved by a modular, image enhancement procedure driven by the image content, which can be combined to improve the overall quality according to image and defect categories.
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- Using recovered reflectance to predict color2
A new method is proposed, based on the reconstruction of multispectral data, for modeling illuminant change, that assumes that the problem is specific for a domain of colors, and that this domain can be modeled in a three dimensional Gaussian space.
- Using genetic algorithms for spectral-based printer characterization2
This work reports here the experimentation on the use of genetic algorithms to tune a spectral printer model based on the Yule-Nielsen modified Neugebauer equation, to obtain a procedure that can spectrally characterize any printer, regardless of the paper and the printer driver used.
- Spectral-Based Characterization of Inkjet Printers by Neural and Genetic Algorithms2
The objective of this work is to see whether the use of methods such as genetic algorithms and neural networks is an effective strategy to approach the complex problem of printer spectral modeling.
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- Approximating the CIECAM97s color appearance model by means of neural networks2
It is shown that it is sufficient to train a single neural network to approximate the combination of the forward and reverse CIECAM97s models independently by the adopted whites and the type of medium (CRT and hard copy).
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- Boosting Learning Algorithms for the Colorimetric Characterization of Color Printers2
The results show that the MPLs can not be effectively boosted, while multiple polynomial regression can be effective, and the accuracy obtained for both transformations from CIELAB to CMY and viceversa is good, but not sufficient for high quality color reproduction.
- Cross-media color matching using neural networks2
Experimental results confirming the feasibility of a practical approach to accurate color reproduction, integrating colorimetric and interactive methods by means of feed-forward neural networks trained by back-propagation are reported.
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- Search and Replace of 2-D Objects in Digital Images2
The “paintbrush” programs currently available make it possible to create and manipulate pictures on a screen in a way that is conceptually similar to the artist’s traditional drawing on paper, but leave to manual intervention all manipulations concerning the shape of objects.
- Multiscale RGB-Guided Fusion for Hyperspectral Image Super-Resolution1
CGNet, a color-guided hyperspectral super-resolution network that leverages complementary information from low-resolution hyperspectral inputs and high-resolution RGB images, achieves higher PSNR and SSIM, lower SAM, and reduced ΔE00, confirming its ability to recover sharp spatial structures while preserving spectral fidelity.
- Illuminant-Adaptive 3D Lookup Tables for Camera Color Correction1
This work proposes a color correction framework based on illuminant-adaptive three-dimensional lookup tables (LUTs), which it calls Color Correction LUT (C$^2$LUT), which combines a chromaticity-aware illuminant representation with a non-linear color transformation, enabling accurate correction under illuminants spanning a wide range of chromaticities and spectral complexities.
- Decoupling spatial and spectral features for efficient hyperspectral image super-resolution1
The proposed Efficient Spatial-Spectral Processing Network (ESSPN) is a lightweight deep learning architecture designed to address the challenges of HSI-SR in a computationally efficient way and shows strong generalization across hyperspectral cameras with varying spectral responses, and across radiometric domains.
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- Scalable Residual Laplacian Network for HEVC-compressed Video Restoration1
A novel Convolutional Neural Network that exploits the Laplacian decomposition technique, which is typically used in traditional image processing, to restore videos compressed with the High-Efficiency Video Coding (HEVC) algorithm with a lower model complexity and shorter runtime with respect to existing methods.
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- DIY absolute tele-colorimeter using a camera-projector system1
A novel approach for colorimetric camera characterization is presented, which exploits a commonly available projector as controllable light source, and accurately relates the camera sensor response to the known reflected radiance.
- On the Importance of Domain Adaptation in Texture Classification1
This paper is the first study investigating up to which extent this visual recognition problem suffers from this issue, and the effectiveness of existing domain adaptation algorithms in mitigating it, and focuses on domain adaptation methods based on shallow classifiers.
- RGB-D-λ: 3D Multispectral Acquisition with Stereo RGB Cameras1
The main criteria defined by COSCH Working Group 1 and used by the authors to help Digital Cultural Heritage users to have a deepen knowledge and understanding of the constraints, preconditions and practical aspects related to the use of a multi-spectral acquisition system are summarized.
- Computational color imaging : 5th International Workshop, CCIW 2015, Saint Etienne, France, March 24-26, 2015 : proceedings1
A Dynamic Relighting System for Moving Planar Objects with Unknown Reflectance is developed and experimental analysis for modeling color of halftone images is conducted.
- Searching through photographic databases with QuickLook1
The prosemantic features are obtained by a two-step feature extraction process and are used as input to a bank of classifiers, each one trained to recognize a given semantic category, to produce score vectors.
- Spatially organized visualization of image query results1
This work presents a system which visualizes the results obtained from image search engines in such a way that users can conveniently browse the retrieved images.
- Bio-inspired framework for automatic image quality enhancement1
This study shows that it is possible to correlate no-reference visual quality values to specific parameter settings such that the quality of an image could be effectively enhanced through the restoration algorithm.
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- Automatic annotation of outdoor photographs1
A strategy for the automatic annotation of outdoor photographs using a normalized cut segmentation to identify the regions to be classified by a multi-class Support Vector Machine.
- Adaptive contrast enhancement for underexposed images1
The goal of this work is to integrate contrast enhancement and denoise algorithms to proper enhance the contrast of images with low illumination that present large underexposed regions.
- On the Coöperative Creation of Multimedia Meaning1
A content-based method for semi- automatic organization of photo albums based on the analysis of how different users organize their own pictures to help the user in dividing his pictures into groups characterized by a similar semantic content.
- Computational Color Imaging: Second International Workshop, CCIW 2009, Saint-Etienne, France, March 26-27, 2009. Revised Selected Papers1
A Computationally Efficient Technique for Image Colorization and an Adaptive Tone Mapping Algorithm for High Dynamic Range Images are presented.
- Computational Color Imaging. Second International Workshop, CCIW 20091
A Computationally Efficient Technique for Image Colorization and an Adaptive Tone Mapping Algorithm for High Dynamic Range Images are presented.
- Matrixing, number of color channels, and color gamut of camera devices1
The relationship between matrixing methods, the number of filters adopted and the size of the color gamut of a digital camera is investigated and an original method developed by the authors is considered.
- FaceLab: a tool for performance evaluation of face recognition strategies1
FaceLab is presented, an innovative, open environment created to evaluate the performance of face recognition strategies, which simplifies the basic steps involved in testing procedures such as data organization and preprocessing, definition and management of training and test sets, definition of recognition strategies and automatic computation of performance measures.
- Accounting for Inks Interaction in the Yule-Nielsen Spectral Neugebauer Model1
A novel strategy to model dot gain and interaction among inks in the definition of a printer model based on the Yule-Nielsen spectral Neugebauer equation is presented, designed for a four-ink ink jet printer, but its formulation is general and may be extended to the characterization of devices having more than four inks.
- Tri-dimensional face detection and localization1
An innovative method that combines a feature-based approach with a holistic approach for tri-dimensional face detection and localization and has been tested on about 150 3D faces acquired by a laser range scanner with good results.
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- An experience in multispectral mosaicing1
This experience was a first attempt at developing a mosaicking framework for multispectral images, including a suitable outline of the flow of operations as well as the selection of methods and procedures for geometrical registration and color synchronization.
- Acquisition, mosaicking and faithful rendering of multispectral images of cultural artifacts1
A general framework for this use is outlined, including mosaicking capabilities for the acquisition of large scenes, and the characteristics and suitability of available multispectral imaging systems are discussed.
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- Pictorial Editing by Shape Matching Techniques1
An original method for providing a pictorial editor with the “search‐and‐replace” facility, that works rather like text substitution in a word processor, based on a model‐driven matching technique.
- Description-Based Image Interpretation as a Tool for Heuristic Inference: A Geological Application1
The interpretation of gravimetric surveys combines with other methodologies such as the interpretation of seismic and magnetic surveys, on-the-spot exploration, etc., to create a geological model of the region in question to provide a great deal of information on below-ground tectonics.
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- Face anonymization preserving facial expressions and photometric realism–
This work proposes a feature-preserving anonymization framework that extends DeepPrivacy by incorporating dense facial landmarks to better retain expressions, and by introducing lightweight post-processing modules that ensure consistency in lighting direction and skin color.
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- Vehicle Pose Estimation: Exploring Angular Representations–
This paper introduces two architectures that approach azimuth estimation as a regression problem, each employing a deep convolutional neural network (DCNN) backbone but diverging in their output definition strategies.
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- A unified platform for GIS data management and analytics–
The platform is designed in such a way that it can easily handle proximity, airborne and spaceborne data and provides to the final user all the tools and proper visualizations to perform precision agriculture.
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- Special Section Guest Editorial: Computational Color Imaging–
This guest editorial introduces the JEI Special Section on Computational Color Imaging and its applications in medicine, education, and research.
- Special Section Guest Editorial:Color in Texture and Material Recognition–
This PDF file contains the editorial “Special Section Guest Editorial: color in Texture and Material Recognition” for JEI Vol.
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- Image Indexing Using Prosemantic Features–
Target search experiments show that the use of prosemantic features, combined with the relevance feedback mechanism of QuickLook, allows for a more successful and quick retrieval of the query images with respect to low-level features.
- High-Level Features for Image Indexing and Retrieval–
Image indexing for content-based image retrieval is the process of automatically computing a compact representation (numerical or alphanumerical) of some attribute of digital images, to be used to derive information about the image contents.
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- Plenary lecture VI: content aware image processing–
According to this approach, the overall quality of a digital photo is improved by modular, fully automatic, image enhancement procedures driven by the image class and content.
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- Exploiting CART methodology in digital color imaging: summary of an experience–
The experience in the use of CART methodology for the automatic semantic classification of digital images based on low-level features describing some of their pictorial characteristics is summarized.
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- Preface–
Cutting-edge material on the latest methods and studies on “data-driven” and “knowledge-based” analysis from the internationally recognized leaders in this field are collected.
- Color image processing and analysis–
Pattern Recognition Letters is concerned with Color image processing and analysis and its applications in medicine, education, and research.
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- Special Section on Internet Imaging–
The issues the authors are interested inexploring pertain to all aspects of the total system, not just images or imag-ing algorithms, and this emphasis on systems is what sets internet imaging apart from other forms of electronic imaging.
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- An Integrated Multimedia System with Learning Capabilities–
The main features of the multimedia information retrieval engine of Quicklook are described, which allows the user to query image and multimedia databases with the aid of sample images, or a user-made sketch and/or textual descriptions, and progressively refine the system's response by indicating the relevance, or non-relevance of the retrieved items.
- Detecting Visual Feature Importance Via TreeClassifiers. An Experience–
This work presents an experience of using tree classifiers as a tool of multivariate exploratory analysis for identifying low-level visual features suitable to capture salient aspects of the semantic content of the images.
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- Retrieving similar color images–
The basic idea is to exploit image data decomposition and compression based on the standard Haar multiresolution wavelet transform to describe image content to effectively eliminate data redundancy and concisely represent the salient features of the image in image signatures of predefined lengths.
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- Using Hopfield networks to segment color images–
Two algorithms for color image segmentation based on Huang's idea of describing the segmentation problem as the one of minimizing a suitable energy function for a Hopfield network are presented.
- Nominal Color Coding of Classified Images by Hopfield Networks–
The experimental evidence that color greatly increases the observer’s understanding of the information contained in a picture and his capacity for remembering it, has led to assigning color a fundamental role in conveying qualitative information in graphical environment.
- Computer Aided Coior'Coding–
A color coding system based on the mental principles of human vision that prevents the user from making mistakes in coding, while guaranteeing the possibility of reproducing them on different devices is described here.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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