A Texture Images Segmentation Method Based on ICA Filters

In this paper we present a feature extraction approach by using ICA filters bank, which consists of the ICA basis images learned from the training images. On the basis of its ability to capture the inherent properties of textured image, we use the ICA filters bank as template model to extract the texture feature for segmentation. Experiments based on clustering and classifications are demonstrated to show the feasibility of this method.