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Proceedings Paper

A model of the formation of a self-organized cortical representation of color
Author(s): A. Ravishankar Rao; Guillermo Cecchi; Charles Peck; James Kozloski
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Paper Abstract

In this paper we address the problem of understanding the cortical processing of color information. Unravelling the cortical representation of color is a difficult task, as the neural pathways for color processing have not been fully mapped, and there are few computational modelling efforts devoted to color. Hence, we first present a conjecture for an ideal target color map based on principles of color opponency, and constraints such as retinotopy and the two dimensional nature of the map. We develop a computational model for the cortical processing of color information that seeks to produce this target color map in a self-organized manner. The input model consists of a luminance channel and opponent color channels, comprising red-green and blue-yellow signals. We use an optional stage consisting of applying an antagonistic center-surround filter to these channels. The input is projected to a restricted portion of the cortical network in a topographic way. The units in the cortical map receive the color opponent input, and compete amongst each other to represent the input. This competition is carried out through the determination of a local winner. By simulating a self-organizing map for color according to this scheme, we are largely able to achieve the desired target color map. According to recent neurophysiological findings, there is evidence for the representation of color mixtures in the cortex, which is consistent with our model. Furthermore, an orderly traversal of stimulus hues in the CIE chromaticity map correspond to an orderly spatial traversal in the primate cortical area V2. Our experimental results are also consistent with this biological observation.

Paper Details

Date Published: 18 March 2005
PDF: 10 pages
Proc. SPIE 5666, Human Vision and Electronic Imaging X, (18 March 2005); doi: 10.1117/12.585526
Show Author Affiliations
A. Ravishankar Rao, IBM Thomas J. Watson Research Ctr. (United States)
Guillermo Cecchi, IBM Thomas J. Watson Research Ctr. (United States)
Charles Peck, IBM Thomas J. Watson Research Ctr. (United States)
James Kozloski, IBM Thomas J. Watson Research Ctr. (United States)

Published in SPIE Proceedings Vol. 5666:
Human Vision and Electronic Imaging X
Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Scott J. Daly, Editor(s)

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