Image segmentation using adaptive balloon force snake model

被引：0

作者：

Shen, Xuan-Jing ^{[1
,2
]}

Wang, Kai-Ye ^{[1
,2
]}

Qian, Qing-Ji ^{[3
]}

Liu, Ying-Jie ^{[4
]}

Li, Xiang ^{[4
]}

机构：

[1] College of Computer Science and Technology, Jilin University, Changchun 130012, China

[2] Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China

[3] College of Physics, Jilin University, Changchun 130022, China

[4] Jilin Songyuanshi Telecom Branch, China Telecom Group Co., Ltd., Songyuan 138000, China

来源：

Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2011年 / 41卷 / 05期

关键词：

Balloons - Fuzzy clustering;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The balloon force snake model is sensitive to the location of initial contour and has the shortcoming of weak boundary leakage. An adaptive balloon force snake model based on fuzzy clustering is proposed. This model integrates global information of the image into the balloon force snake model, and is used for image segmentation. It can adaptively change the direction and magnitude of the balloon force according to regional information, which makes the contour converge to the target boundary correctly. Experiment results show that the proposed model has lower restriction on the location of the initial contour and overcome the shortcoming of weak boundary leakage. Therefore, the contour can converge on concave boundary correctly. Furthermore, the improved model has strong robustness to noise and has no critical point problem of Gradient Vector Flow (GVF).

引用

页码：1394 / 1400