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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.

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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Bottom-up visual saliency In this project, we obtain saliency maps from color images using perceptual characteristics.

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Color-Texture descriptors We propose color-texture descriptors that are directly based on a perceptual theory of texture discrimination (Julesz’s Texton Theory).

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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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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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