| WANG Jing,ZHENG Yong-guo,PAN Zhen-kuan,ZHANG Wei-zhong,WANG Guo-dong.A multiphase texture segmentation method based on local intensity distribution and Potts model[J].Optoelectronics Letters,2015,11(4):307-312 |
| A multiphase texture segmentation method based on local intensity distribution and Potts model |
| Author Name | Affiliation | | WANG Jing | College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China
College of Information Engineering, Qingdao University, Qingdao 266071, China | | ZHENG Yong-guo | College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China | | PAN Zhen-kuan | College of Information Engineering, Qingdao University, Qingdao 266071, China | | ZHANG Wei-zhong | College of Information Engineering, Qingdao University, Qingdao 266071, China | | WANG Guo-dong | College of Information Engineering, Qingdao University, Qingdao 266071, China |
|
| Abstract: |
| Because texture images cannot be directly processed by the gray level information of individual pixel, we propose a new texture descriptor which reflects the intensity distribution of the patch centered at each pixel. Then the general multiphase image segmentation model of Potts model is extended for texture segmentation by adding the region information of the texture descriptor. A fast numerical scheme based on the split Bregman method is designed to speed up the computational process. The algorithm is efficient, and both the texture descriptor and the characteristic functions can be implemented easily. Experiments using synthetic texture images, real natural scene images and synthetic aperture radar images are presented to give qualitative comparisons between our method and other state-of-the-art techniques. The results show that our method can accurately segment object regions and is competitive compared with other methods especially in segmenting natural images. |
| Hits: 3806 |
| Download times: 0 |
| This work has been supported by the National Natural Science Foundation of China (No.61170106). |
| View Full Text Download reader |
|
|
|
