Integrated Approach to Texture Segmentation

This paper presents an integrated approach using multiple Gabor lters for the segmentation of multi-textured images. The approach includes both the design of the constituent Gabor lters and the design of the classiier and postprocessing. The classiier uses a mixture density to reduce localization error at texture boundaries, and the post-processing uses morphological operators to remove spurious misclassiications at texture boundaries. Results are presented that connrm the eecacy of the postprocessing methods and the overall integrated approach.