Dufort P A, Lumsden C J
Department of Medicine, University of Toronto, Canada.
Biol Cybern. 1991;65(4):293-303. doi: 10.1007/BF00206226.
We develop a neural network model that instantiates color constancy and color categorization in a single unified framework. Previous models achieve similar effects but ignore important biological constraints. Color constancy in this model is achieved by a new application of the double opponent cells found in the "blobs" of the visual cortex. Color categorization emerges naturally, as a consequence of processing chromatic stimuli as vectors in a four-dimensional color space. A computer simulation of this model is subjected to the classic psychophysical tests that first uncovered these phenomena, and its response matches psychophysical results very closely.
我们开发了一种神经网络模型，该模型在一个统一的框架中实现了颜色恒常性和颜色分类。以前的模型也能达到类似的效果，但忽略了重要的生物学限制。该模型中的颜色恒常性是通过对视觉皮层“斑点”中发现的双拮抗细胞的新应用来实现的。颜色分类自然出现，这是在四维颜色空间中将色度刺激作为向量进行处理的结果。对该模型进行计算机模拟，并使其接受最初发现这些现象的经典心理物理学测试，其反应与心理物理学结果非常接近。
