A new fuzzy segmentation approach based on S-FCM type 2 using LBP-GCO features

作者：Tlig Lotfi^*; Sayadi Mounir; Fnaiech Farhat

来源：Signal Processing: Image Communication , 2012, 27(6): 694-708.

DOI：10.1016/j.image.2012.03.001

• Texture segmentation
• Gabor filter
• Local binary pattern
• Fuzzy clustering

Gabor filtering is a widely applied approach for texture analysis. This technique shows a strong dependence on certain number of parameters. Unfortunately, each variation of values of any parameter may affect the texture characterization performance. Moreover, Gabor filters are unable to extract micro-texture features which also have a negative effect on the clustering task. This paper, deals with a new descriptor which avoids the drawbacks mentioned above. The novel texture descriptor combines grating cell operator outputs derived from a designed Gabor filters bank, and local binary pattern features. For the clustering task, an extended version of fuzzy type 2 clustering algorithm is also proposed. The effectiveness of the proposed segmentation approach on a variety of synthetic and textured images is highlighted. Several experimental results on a set of textured images show the superiority of the proposed approach in terms of segmentation accuracy with respect to quantitative and qualitative comparisons.

• 出版日期2012-7