The purpose of this study is to get a color perception model of dichromat. We construct a color perception model of dichromat, and analyze the mechanism. Then we have prospect of find human color perception mechanism. We expect it when we understand mechanism of the color perception of the human beings by construct and analysis a dichromat's color perception model. We construct a color perception model of color defects based on the results of psychophysical experiments with optimizes the structure of neural network using genetic algorithm (GA). The neural network used in this paper is real valued flexibly connected neural network (RFCN). RFCN, the evolutionary neural network we previously proposed, is a model that can have high performance in various fields. In RF CN, the structure of the network and the parameter are optimized automatically and flexibly with GA according to tasks we give. So we can obtain the network that has desirable performance without special knowledge about the task. We developed a model that can operate similarly to dichromat's categorical color perception. The results showed that the obtained neural network has similar characteristics to those of dichromat's vision system.
Noriko Yata, Tomoharu Nagao, Keiji Uchikawa, "Dichromat's Categorical Color Perception Model" in Proc. IS&T CGIV 2012 6th European Conf. on Colour in Graphics, Imaging, and Vision, 2012, pp 295 - 300, https://doi.org/10.2352/CGIV.2012.6.1.art00051