An active contours method based on intensity and reduced gabor features for texture segmentation

Authors:
Huchuan Lu;Yunyun Liu;Zhipeng Sun;Yenwei Chen
Affiliations:
Dalian University of Technology, Department of Electronic Engineering Dalian, China;Dalian University of Technology, Department of Electronic Engineering Dalian, China;Dalian University of Technology, Department of Electronic Engineering Dalian, China;Dalian University of Technology, Department of Electronic Engineering Dalian, China and Ritsumeikan University, College of Information Science and Engineering, Kyoto, Japan
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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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.