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AN ACTIVE CONTOURS METHOD BASED ON INTENSITY AND REDUCED GABOR FEATURES FOR TEXTURE SEGMENTATION

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Indexed by:会议论文

Date of Publication:2009-11-07

Included Journals:EI、CPCI-S、Scopus

Page Number:1369-1372

Key Words:Texture segmentation; level set; active contour without edges; Gabor filter

Abstract:In this paper, we propose a cooperative strategy for segmentation of texture images which integrates reduced Gabor features and image components. In contrast with the structure tensor method, our algorithm can extract more important features for segmentation. In this work, Gabor filters tuned to a set of orientations, scales and frequencies are used to extract texture local features, and the vector-valued active contour without edges model is employed to segment images. The main contribution of this work is the cooperation of image components and the reduced Gabor features which are extracted by principal components analysis (PCA) to represent image features. This cooperation improves the quality of the method, since the segmentation is faster and better. We demonstrate the effectiveness of our algorithm by comparing with the method proposed by Wang for segmenting synthetic and nature texture images.

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