Integrating clustering with level set method for piecewise constant Mumford-Shah model

被引：0
作者：
Qiang Chen
Chuanjiang He
机构：
[1] Chongqing University,College of Mathematics and Statistics
来源：
EURASIP Journal on Image and Video Processing | / 2014卷
关键词：
Image segmentation; Mumford-Shah model; Alternating optimization; Level set method; Clustering algorithm;
D O I：
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学科分类号：
摘要：
In the paper, we present an efficient method to solve the piecewise constant Mumford-Shah (M-S) model for two-phase image segmentation within the level set framework. A clustering algorithm is used to find approximately the intensity means of foreground and background in the image, and so the M-S functional is reduced to the functional of a single variable (level set function), which avoids using complicated alternating optimization to minimize the reduced M-S functional. Experimental results demonstrated some advantages of the proposed method over the well-known Chan-Vese method using alternating optimization, such as robustness to the locations of initial contour and the high computation efficiency.
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