Edge detection combined entropy threshold and self-organizing map (SOM)

被引：0

作者：

Wang, Kun ^{[1
]}

Gao, Liqun ^{[1
]}

Pian, Zhaoyu ^{[1
]}

Guo, Li ^{[1
]}

Wu, Jianhua ^{[1
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, POB 135, Shenyang 110004, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2007, PT 2, PROCEEDINGS | 2007年 / 4492卷

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：

An edge detection method by combining image entropy and Self -Organizing Map (SOM) is proposed in this paper. First, according to information theory image entropy is used to curve tip the smooth region and the region of gray level abruptly changed. Then we transform the gray level image to ideal binary pattern of pixels. We define six classes' edge and six edge prototype vectors. These edge prototype vectors are fed into input layer of the Self-Organizing Map (SOM). Classifying the type of edge through this network, the edge image is obtained. At last, the speckle edges are discarded from the edge image. Experimental results show that it gained better edge image compared with Canny edge detection method.

引用

页码：931 / +

页数：2

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