Novel approaches to multichannel filtering for image texture segmentation

Abstract

Abstract Several approaches to multichannel filtering for texture classification and segmentation with Gabor filters havebeen proposed. The rationale presented for the use of the Gabor filters is their relation to models for the earlyvision of mammals as well as their joint optimum resolution in time and frequency. In this work we present acritical evaluation of the Gabor filters as opposed to filter banks used in image coding — in both full rate and critically sampled realizations. In the critically sampled case, tremendous computational savings can be realized.We further evaluate the commonly used octave band decomposition versus alternative decompositions.We conclude that for a texture segmentation task is it possible to use a wider range of filters than just theGabor class of filters, it is possible to use alternative decompositions and, most important, it is possible to usesubsampled filters. 1 Introduction In several recent papers the successful application of multichannel filtering for texture segmentation is reported [1,2, 3, 4, 5, 6, 7]. The channel filters utilized are Gabor filters [8] designed to respond to different spatial frequencies.The rationale presented for the use of the Gabor filters is their relation to models for the early vision of mammals aswell as their joint optimum resolution in time and frequency [8, 9] .