Evaluating multiscale opponent color features using Gabor filters

We introduce a representation for color texture using unichrome and opponent features computed from Gabor filter outputs. The unichrome features are computed from the spectral bands independently while the opponent features combine information across different spectral bands at different scales. Opponent features are motivated by color opponent mechanisms in human vision. We present a method for efficiently implementing these filters which is of particular interest for processing the additional information present in color images. Using a database of 2560 image regions, we show that the multiscale approach using opponent features provides better recognition accuracy than other approaches.