Gabor Filtering of Complex Hue/Saturation Images for Color Texture Classification

Objective: Complex hue/saturation images as a new approach for color texture classification using Gabor filters are introduced and compared with common techniques. Method: The interpretation of hue and saturation as polar coordinates allows direct use of the HSVcolorspace for Fourier transform. This technique is applied for Gabor feature extraction of color textures. In contrast to other color features based on the RGB-colorspace [1] the combination of color bands is done previous to the filtering. Results: The performance of the new HS-features is compared with that of RGB based as well as grayscale Gabor features by evaluating the classification of 30 natural textures. The new HS-features show same results like the best RGB features but allow a more compact representation. On the average the color features improve the results of grayscale features. Conclusion: The consideration of the color information enhances the classification of color texture. The choice of colorspace cannot be adjudged finally, but the introduced features suggest the use of the HSV-colorspace with less features than RGB.