传统的色度学系统是建立在人类视觉系统的心理物理实验基础上的，共有基于实验的色标系统（如MUNSELL颜色体系）和基于实验的经验公式系统（如CIELAB，CIELUV体系）二类体系。但是，人类颜色视觉系统的色度学体系及相应的颜色测量方法并不适合于机器视觉系统，因为人类色度学体系的颜色空间是非均匀空间，即色度图上两点之间的欧氏距离并不能代表颜色知觉的差异，由于两者存在着非线性关系，为此，提出将现代计算机礼堂中关于环境光照和物体表面的物理模型引入经典的色度学，以建立一套新的基于物理模型的虚拟颜色空间，用于标定不同颜色视觉系统的颜色率。

The measurement of color difference in machine vision is the basement of image segmentation based on the color features, but there is no colorimetrical system for machine vision. Traditional colorimetry has two major systems: (1) to build a color specification system experimentally and to use it as a reference (for example, the Munsell Book of Color). (2) to develop an analytical formulation based on discrimination experiments (such as, CIELAB, CIELUV). The color space based on the psychophysical experiments of human visual system is non-flat. That means the perceptual difference of colors can not be described by the Euclidian distances between the related two points in the color space and the map from perceptual difference to the Euclidian distances is not linear. In this paper, we built a virtual color space based on the physical models of light, reflectance of surfaces and the sampling function of visual system. In this virtual color space the chromatism of machine vision can be calculated linearly. We also suggest that the chromatism measurement of machine vision is different from the spectral reflectance of physical surfaces used in present computer models of color vision.