MRF model based image segmentation using hierarchical distributed genetic algorithm

被引：17

作者：

Kim, HJ ^{[1
]}

Kim, EY ^{[1
]}

Kim, JW ^{[1
]}

Park, SH ^{[1
]}

机构：

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

来源：

ELECTRONICS LETTERS | 1998年 / 34卷 / 25期

关键词：

D O I：

10.1049/el:19981674

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 for segmenting noisy and blurred images is proposed. A Markov random field (MRF) model is used which is robust to degradation. Since this is computationally intensive, a hierarchical distributed genetic algorithm (HDGA) is used which is unsupervised and parallel. Experimental results show that the proposed method is effective at segmenting real images.

引用

页码：2394 / 2395

页数：2

共 6 条

[1] STOCHASTIC RELAXATION, GIBBS DISTRIBUTIONS, AND THE BAYESIAN RESTORATION OF IMAGES [J].

GEMAN, S ;

GEMAN, D .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1984, 6 (06) :721-741

[2] IMAGE SEGMENTATION USING SIMPLE MARKOV FIELD MODELS [J].

HANSEN, FR ;

ELLIOTT, H .

COMPUTER GRAPHICS AND IMAGE PROCESSING, 1982, 20 (02) :101-132

[3] EFFICIENT IMAGE LABELING BASED ON MARKOV RANDOM-FIELD AND ERROR BACKPROPAGATION NETWORK [J].

KIM, IY ;

YANG, HS .

PATTERN RECOGNITION, 1993, 26 (11) :1695-1707

[4] Hierarchical distributed genetic algorithms: A fuzzy logic controller design application [J].

Kim, J ;

Zeigler, BP .

IEEE EXPERT-INTELLIGENT SYSTEMS & THEIR APPLICATIONS, 1996, 11 (03) :76-84

[5]

KIM JW, 1997, ACCV 98, V1, P730

[6]

LIN JK, 1994, IEEE T PATTERN ANAL, V16, P689

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