Texture segmentation using Gabor filters

In this paper an unsupervised texture segmentation technique using multi-channel filtering has been proposed. The main advantage of this approach is that it can use simple statistics of gray values in the filtered images as texture features. This simplicity is due to direct result of decomposition of the original image into several filtered images with limited spectral information. The main issues involved in this approach are: 1) functional characterization of the channels and number of channels, 2) extraction of appropriate texture features from the filtered images, 3) the relationship between the channels, and 4) integration of texture features from different channels to produce a reliable segmentation.