Color Texture Image Segmentation Using Chromatic Statistical Landscape Features
CHEN YunWen1,2, XU CunLu2
1.Department of Computer Science and Engineering, Fudan University, Shanghai 200433 2.School of Information Science and Engineering, Lanzhou University, Lanzhou 730000
Abstract Texture analysis is a nodus in computer vision and pattern recognition. A novel approach for color texture segmentation is proposed, called chromatic statistical landscape features (CSLF). An equiangular mapping process is used to transform an HSI space image into some pseudogray images, which can be regarded as the surfaces of the corresponding 3D landscapes. Variable horizontal planes are used to slice them. The statistic features are extracted from the set of solids which are introduced by the slicing. A supervised estimation algorithm based on Mahalanobis distance is employed for segmentation. Experimental results obtained on VisTex dataset, synthetic image and remote sensing image are presented and evaluated, which demonstrate the feasibility of the proposed method.
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2007, Vol. 20 
