Image Segmentation Using Binary Level Set Method Based on Region-based GAC Model

被引:2
|
作者
Ren Ge [1 ]
Cao Xing-Qin [1 ]
Pan Wei-Min [1 ]
Yang Yong [1 ]
机构
[1] Xinjiang Normal Univ, Coll Comp Sci, Wulumqi, Peoples R China
关键词
image segmentation; level set; active contours; re-initialization;
D O I
10.4028/www.scientific.net/KEM.480-481.1206
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A new Region-based GAC (geodesic active contour) model was presented, which is the improvement of traditional GAC model. A new region-based signed pressure forces function was presented, which takes the place of the edge stopping function, and can efficiently solve the problem of segmentation of objects with weak edges or without edges. The model is implemented by level set method with a binary level set function to reduce the expensive computational cost of re-initialization of the traditional level set function. The proposed algorithm has been applied to images of different modalities with promising results, which are better than that of traditional GAC model and C-V model.
引用
收藏
页码:1206 / 1209
页数:4
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