A new image texture extraction algorithm based on matching pursuit Gabor wavelets

Feature vector extraction, based on local image texture, is a primitive algorithm for many other applications, like segmentation, clustering and identification. If these feature vectors are a good match to the human visual system (HVS), we can expect to get the appropriate results by using them. Gabor filters have been used for this purpose successfully. In this paper we introduce a novel refinement, with the use of matching pursuits (MP) to improve the Gabor based texture feature extractor. With this improvement, we show that the separability of different textures increases. Another consideration in this work is computation complexity. Therefore, we limit the basis function set to reduce MP computation time.