Unsupervised Color Texture Feature Extraction and Selection for Soccer Image Segmentation

In this paper, we describe a new approach for color texture feature extraction and selection. We define color texture features as texture features which are computed by taking into account the color components of the pixels. We determine the most discriminating color texture features among a multidimensional set of color texture features by means of an iterative feature selection procedure associated to an information criterion. This procedure analyses images which are classified by a competitive learning scheme. Soccer image segmentation is achieved by pixel classification. The classification algorithm takes into account these color texture features which are processed in the neighborhood of the pixels. We apply our new unsupervised approach to soccer images segmentation.