Design of multiple Gabor filters for texture segmentation

This paper presents a method for the design of multiple Gabor filters for segmenting multi-textured images. Although design methods for a single Gabor filter have been presented recently, the development of general multi-filter multi-texture design methods largely remains an open problem. Previous multi-filter design approaches required one filter per texture or were constrained to pairs of textures. Other approaches employed ad hoc banks of Gabor filters for texture segmentation, where the parameters of the constituent filters were restricted to fixed values and were not necessarily tuned for a specific texture-segmentation problem. The proposed method removes these restrictions on the number of filters and the number of textures. This offers the potential to improve the segmentation performance or to reduce the number of filters. Further, the development of the design method and mathematical models provide new insight into the design of multiple Gabor filters for texture segmentation. Results are presented that confirm the efficacy of our filter-design method and support underlying mathematical models.