Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimized multichannel filter bank with flat frequency response for texture segmentation
EURASIP Journal on Applied Signal Processing
Texture based prelens tear film segmentation in interferometry images
Machine Vision and Applications
Texture-based filtering and front-propagation techniques for the segmentation of ultrasound images
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
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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 previously, 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.