Image Segmentation Based on Local Region LBP algorithm
被引:0
|
作者:
Xu Shengjun
论文数: 0引用数: 0
h-index: 0
机构:
Xian Univ Architectural & Technol, Sch Informat & Control Engn, Xian, Peoples R China
Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian, Peoples R ChinaXian Univ Architectural & Technol, Sch Informat & Control Engn, Xian, Peoples R China
Xu Shengjun
[1
,2
]
Lin Qunying
论文数: 0引用数: 0
h-index: 0
机构:
Shannxi Telecom, Xian, Peoples R ChinaXian Univ Architectural & Technol, Sch Informat & Control Engn, Xian, Peoples R China
Lin Qunying
[3
]
Liu Xin
论文数: 0引用数: 0
h-index: 0
机构:
Xian Univ Architectural & Technol, Sch Informat & Control Engn, Xian, Peoples R ChinaXian Univ Architectural & Technol, Sch Informat & Control Engn, Xian, Peoples R China
Liu Xin
[1
]
机构:
[1] Xian Univ Architectural & Technol, Sch Informat & Control Engn, Xian, Peoples R China
[2] Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian, Peoples R China
component;
Image segmentation;
Energy minimization;
Markov random fields;
LBP algorithm;
MARKOV RANDOM-FIELDS;
D O I:
暂无
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
A method for image segmentation was presented which based on LBP(Loopy Belief Propagation) of local region energy minimization. Based on global energy minimization for image segmentation by traditional LBP algorithm, the proposed method used local region energy as the messages of LBP algorithm, and combined global energy minimization with local region energy minimization, so improved the efficiency of messages passing in LBP algorithm. In the experiments, the proposed method is compared with the traditional LBP algorithm. Experiments on natural images showed that the proposed method is able to obtain more accurate segmentation results and also less sensitive to noise than some of the existing models in common use.