A comparison of texture feature extraction using adaptive gabor filtering, pyramidal and tree structured wavelet transforms

In recent studies on image analysis an increasing effort has been carried out in the area of wavelet transform techniques for the discrimination and classification of textural images. These methods compete with multichannel filtering techniques, especially with the nonorthogonal and incomplete Gabor filtering. In this paper we introduce two feature extraction algorithms based on pyramidal and tree structured wavelet transforms and compare their performance with that of feature extraction which employs adaptive Gabor filtering. This comparison is based on the segmentation results of several texture image examples using the identical segmentation algorithm for all three feature extraction methods. The visible differences of the segmentation results are discussed and their algorithmic causes are analysed.