Texture Segmentation Based on Image Model and Neural Network

被引：0
|
作者：
Chen Zhenyu
Sheng Wen
Wang Guangjun
Li Dehua(State Education Commission Laboratory for Image Processing and Intelligence Control
机构：
来源：
Journal of Earth Science | 1999年 / 04期
关键词：
texture analysis; Markov random field; neural network;
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：
This paper presents a texture segmentation approach which is based on the Markov random field model (MRF) and feed forward neural network.Image texture is modeled by the second order Gauss MRF model, and the least square error estimation is employed for the solution of model parameters. To perform texture segmentation, we introduced an improved BP algorithm to get faster learning speed. Experiment shows that better segmentation results can be obtained than the traditional Euclidean distance method.
引用
收藏
页码：333 / 335
页数：3
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