Abstract
Both physiological and psychological evidences suggest that the human visual system analyze images in neural subsystems tuned to different attributes of the stimulus. Color module and lightness module are such subsystems. Under this general result, a new physical model of trichromatic system has been developed to deal with the color constancy of computer vision. A normal color image is split into two images: the gray scale image and the equal lightness color image for the two modules. Relatively, a two-dimensional descriptor is applied to describe the property of surface reflectance in the equal lightness color image. This description of surface spectral reflectance has the property of color constancy. Image segmentation experiments based on color property of object show that the presented model is effective.
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This work is supported by the National ‘863’ High-Tech Programme of China (No. 863-306-03-01-1).
TAO Linmi is the project manager of the EC Project ARROV (Argument Reality for Remotely Operated Vehicles) in University of Verona, Italy. He received his Ph.D. degree in application of computer from Tsinghua University in 2001, his M.S. degree in visual perception from Institute of Biophysics, The Chinese Academy of Sciences in 1991, and his B.S. in biological science from Hangzhou University in 1986. In addition, he visited International Institute for Advanced Scientific Studies, Italy as a Postdoctoral Fellow in 1994. His research interests span a broad spectrum of the fields of visual perception and computer vision, especially of human color perception and machine color vision.
XU Guangyou is the Chair Professor of Institute of Human Computer Interaction and Media Integration, Dept. of Computer Science and Technology, Tsinghua University. He graduated from the Department of Automatic Control Engineering, Tsinghua University, Beijing, China in 1963. His research interests covers computer vision, human computer interaction and multimedia computing.
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Tao, L., Xu, G. A new color constancy model for machine vision. J. Comput. Sci. & Technol. 16, 567–573 (2001). https://doi.org/10.1007/BF02943241
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DOI: https://doi.org/10.1007/BF02943241