Classification of color textures by Gabor filtering
Christoph Palm, Thomas Lehmann · 2002
Abstract. A novel approach to Gabor filtering of color textures is introduced. It is based on the complex chromatic Fourier transform. Complex colors are derived from the HSL color space representing intensity independent color textures. Additionally, a novel Gabor texture feature for the grayscale as well as the color domain is proposed. It relies on local phase changes characterizing the homogeneity of a texture in the spatial frequency domain. Several classification experiments on two image databases are performed to study the texture features according to different color spaces and Gabor filter bank variants. The color features show significantly better results than the grayscale features. Although they are completely intensity independent, the features on basis of the complex color space show satisfying results. The RGB based features, where inherently color and intensity work together, performed best. Especially the local phase change measure supplement the known amplitude measure appropriately.