A Region Merging Prior for Variational Level Set Image Segmentation

被引：29

作者：

Ben Ayed, Ismail ^{[1
]}

Mitiche, Amar ^{[1
]}

机构：

[1] INRS EMT, Montreal, PQ H5A 1K6, Canada

来源：

IEEE TRANSACTIONS ON IMAGE PROCESSING | 2008年 / 17卷 / 12期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Active contours; image segmentation; level sets; segmentation prior;

D O I：

10.1109/TIP.2008.2006425

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In current level set image segmentation methods, the number of regions is assumed to known beforehand. As a result, it remains constant during the optimization of the objective functional. How to allow it to vary is an important question which has been generally avoided. This study investigates a region merging prior related to regions area to allow the number of regions to vary automatically during curve evolution, thereby optimizing the objective functional implicitly with respect to the number of regions. We give a statistical interpretation to the coefficient of this prior to balance its effect systematically against the other functional terms. We demonstrate the validity and efficiency of the method by testing on real images of intensity, color, and motion.

引用

页码：2301 / 2311

页数：11

共 29 条

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[2]

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[3] Multiregion level-set partitioning of synthetic aperture radar images [J].