A genetic algorithm-based segmentation of Markov random field modeled images

被引：27

作者：

Kim, EY ^{[1
]}

Park, SH ^{[1
]}

Kim, HJ ^{[1
]}

机构：

[1] Kyungpook Natl Univ, Dept Comp Engn, Taegu 702701, South Korea

来源：

IEEE SIGNAL PROCESSING LETTERS | 2000年 / 7卷 / 11期

关键词：

distributed genetic algorithm; energy function; Markov random field (MRF);

D O I：

10.1109/97.873564

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：

An unsupervised method is presented for segmenting video sequences degraded by noise. Each frame in a sequence is modeled using a Markov random field (MRF), and the energy function of each MRF is minimized by chromosomes that evolve using distributed genetic algorithms. To improve the computational efficiency, only unstable chromosomes corresponding to moving object parts are evolved. Experimental results show the effectiveness of the proposed method.

引用

页码：301 / 303

页数：3

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