Automatic segmentation based on AdaBoost learning and graph-cuts

被引：0
|
作者：
Han, Dongfeng [1 ]
Li, Wenhui [1 ]
Lu, Xiaosuo [1 ]
Wang, Tianzhu [1 ]
Wang, Yi [1 ]
机构：
[1] Jilin Univ, Coll Comp Sci & Technol, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun 130012, Peoples R China
来源：
IMAGE ANALYSIS AND RECOGNITION, PT 1 | 2006年 / 4141卷
关键词：
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：
An automatic segmentation algorithm based on AdaBoost learning and iterative Graph-Cuts are shown in this paper. In order to find the approximate location of the object, AdaBoost learning method is used to automatically find the object by the trained classifier. Some details on AdaBoost are described. Then the nodes aggregation method and the iterative Graph-Cuts method are used to model the automatic segmentation problem. Compared to previous methods based on Graph-Cuts, our method is automatic. This is a main feature of the proposed algorithm. Experiments and comparisons show the efficiency of the proposed method.
引用
收藏
页码：215 / 225
页数：11
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