Ive been told that it is very important to work in HSI space rather than RGB space. Why does it matter what color space is used?
Many traditional applications of color machine vision are aimed at differentiating single color objects from the background for alignment and gauging purposes. As long as the colors in the image are reasonably well saturated hue will tend to remain relatively constant in the presence of shadows and other lighting variations. In such cases an image based on hue alone may work better with standard alignment and gauging tools than traditional gray scale analysis. Unfortunately, when colors have low saturation (lie near the black-gray-white axis) hue may be difficult to determine accurately; when saturation is zero hue is undefined. For systems which must be able to differentiate all colors, saturated and unsaturated, HSI representation can introduce significant problems. We have found that for general recognition and classification of objects which may be multicolored, contrary to conventional wisdom, the disadvantages of HSI space will almost always outweigh any possible advantages.
