A new unsupervised image segmentation algorithm based on deterministic annealing EM

被引：0

作者：

Zhong, JQ ^{[1
]}

Wang, RS ^{[1
]}

机构：

[1] Natl Univ Def Technol, ATR, Natl Lab, Changsha 410073, Peoples R China

来源：

2003 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS, INTELLIGENT SYSTEMS AND SIGNAL PROCESSING, VOLS 1 AND 2, PROCEEDINGS | 2003年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new unsupervised image segmentation algorithm based on deterministic annealing EM (DAEM) is proposed in this paper The method is based on maximum likelihood (ML) estimation. Image is considered as a mixture of multi-variant normal densities and the number of densities is assumed to know. In order to obtain the parameters of densities, deterministic annealing EM algorithm is introduced. In DAEM algorithm, the EM process is reformulated as the problem of minimizing the thermodynamic free energy by, using a statistical mechanics analogy. Thus, The DAEM algorithm can overcome the local maximize problem of general EM algorithm. The proposed method is successfully applied to image segmentation experiments.

引用

页码：600 / 604

页数：5

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