Title :
Fast Texture Segmentation Based on Semi-local Region Descriptor and Active Contour Driven by the Bhattacharyya Distance
Author :
Zhang, Shanqing ; Xin, Weibin ; Zhang, Guixu
Author_Institution :
Inst. of Graphics & Image, Hangzhou Dianzi Univ., Hangzhou, China
Abstract :
Based on a texture descriptor which intrinsically defines the geometry of textures using semi-local image information and tools from differential geometry, a fast active contour segmentation model for color texture image is proposed. In this model, we use the popular Bhattacharyya distance between the probability density function (pdf) to design the data fitting term which distinguishes the background and textures of interest. Then, a fast algorithm based on the Split-Bregman method is introduced to extract meaningful objects. Finally, some examples on some challenging images are illustrated to verify the possibility of the proposed model.
Keywords :
image colour analysis; image segmentation; image texture; probability; Bhattacharyya distance; Split-Bregman method; active contour segmentation model; color texture image; probability density function; semilocal region descriptor; texture segmentation; Active contours; Image color analysis; Image segmentation; Minimization; Numerical models; Probability density function; Tensile stress; Bhattacharyya flow; Split-Bregman method; active contour; geometry of textures; image segmentation;
Conference_Titel :
Multimedia Information Networking and Security (MINES), 2010 International Conference on
Conference_Location :
Nanjing, Jiangsu
Print_ISBN :
978-1-4244-8626-7
Electronic_ISBN :
978-0-7695-4258-4
DOI :
10.1109/MINES.2010.15