A computational model for texture perception with chromatic and achromatic images

We have developed a new computational model for texture perception which is physiologically plausible and mimics human performance. Our model tries to simulate the visual processing characteristics by incorporating mechanisms tuned to luminance, orientation, spatial-frequency and color, which are characteristic features of any textural image. We obtained a very good correlation between human performance and our model simulations with various strategic texture patterns. The highlights of our model are incorporation of chromatic mechanisms to treat color images, in addition to grey-level ones, and the extension of the concept of double-opponency beyond color. The model could be utilized in the area of image processing, machine vision and pattern recognition, and scientific visualization.<>