Unsupervised texture based image segmentation by simulated annealing using Markov random field and Potts models

被引：0

作者：

Goktepe, M ^{[1
]}

Atalay, V ^{[1
]}

Yalabik, N ^{[1
]}

Yalabik, C ^{[1
]}

机构：

[1] Bilkent Univ, IAED Dept, Fac Art Des & Arch, Ankara, Turkey

来源：

FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2 | 1998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：

Unsupervised segmentation of images which are composed of various textures is investigated A coarse segmentation is achieved through a hierarchical self organizing map. This initial segmentation result is fed into a simulated annealing algorithm in which region and texture parameters are estimated using maximum likelihood technique. Region geometries are modeled as Potts model while textures are modeled as Markov random fields. Tests are performed an artificial textured images.

引用

页码：820 / 822

页数：3