Active contours with neighborhood-extending and noise-smoothing gradient vector flow external force

被引:47
作者
Liu, Lixiong [1 ]
Bovik, Alan C. [2 ]
机构
[1] Beijing Inst Technol, Sch Comp Sci, Beijing Lab Intelligent Informat Technol, Beijing 100081, Peoples R China
[2] Univ Texas Austin, Dept Elect & Comp Engn, Lab Image & Video Engn, Austin, TX 78712 USA
关键词
image segmentation; active contour; gradient vector flow; Laplacian operator; neighborhood-extending and noise-smoothing gradient vector flow; MODELS;
D O I
10.1186/1687-5281-2012-9
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We propose a novel external force for active contours, which we call neighborhood-extending and noise-smoothing gradient vector flow (NNGVF). The proposed NNGVF snake expresses the gradient vector flow (GVF) as a convolution with a neighborhood-extending Laplacian operator augmented by a noise-smoothing mask. We find that the NNGVF snake provides better segmentation than the GVF snake in terms of noise resistance, weak edge preservation, and an enlarged capture range. The NNGVF snake accomplishes this with a reduced computational cost while maintaining other desirable properties of the GVF snake, such as initialization insensitivity and good convergences at concavities. We demonstrate the advantages of NNGVF on synthetic and real images.
引用
收藏
页数:6
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