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The CVC colour group focuses its research in areas related to computational colour within computer vision. Our long term objective is to create computer algorithms that simulate human perception and categorisation of colour. To achieve this aim, we study colour as a visual cue in its context. Our main research lines are colour constancy, induction, saliency, texture,segmentation and naming.

Chromatic Induction We propose a computational model that reprodce chromatic induction processes unifying chromatic assimilation and chromatic contrast into a single perceptual process.

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Image Compression The aim of this work is to apply perceptual concepts to defina a perceptual pre-quantizer in order to improve image compression algorithms.

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Physics-based color image segmentation Based on an analysis of the bi-directional reflection model we propose a method which is particularly suited for segmentation in the presence of shadow and highlight edges.

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Color Feature Detection for Object Recognition Luminance edges are still the main source of information in the state-of-the-art methods for feature detection. We propose to exploit the statistical structure of luminance and color in natural images to extract the most discriminative features from the viewpoint of information theory for object recognition.

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Psychophysical Error Measure for Colour Constancy In this paper we propose a new evaluation in order to compare solutions of different colour constancy algorithms. this new approach is based on a psychophysical experiment to relate this new evaluation with human perception instead of physical properties.

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