Why does WAY-2C succeed where the competition fails?
All competing systems of which we are aware offer color as an extension to their traditional monochrome machine vision products. In contrast, WAY-2C is designed specifically to recognize objects based on their color distributions. It is the product of over a decade of research by a team of Ph.D’s with expertise in optical physics, information theory, and data analysis. Most existing color machine vision systems which offer statistical matching analyze the three color components separately. However both common sense and a rigorous analysis show that this approach throws away critical color information thus dramatically decreasing the number of color patterns which can be distinguished and increasing the probability of errors. Also, traditional statistical matching methods for color machine vision are based on simplifying assumptions about the nature of the color distribution.
