An Improved Unit-Linking PCNN for Segmentation of Infrared Insulator Image

被引：9
作者：
Cui, Kebin [1 ]
Li, Baoshu [2 ]
Yuan, Jinsha [3 ]
Wang, Ping [1 ]
机构：
[1] North China Elect Power Univ, Dept Comp, Baoding 071000, Peoples R China
[2] North China Elect Power Univ, Dept Elect Engn, Baoding 071000, Peoples R China
[3] North China Elect Power Univ, Dept Elect, Baoding 071000, Peoples R China
来源：
APPLIED MATHEMATICS & INFORMATION SCIENCES | 2014年 / 8卷 / 06期
关键词：
Unit-linking PCNN; segmentation; infrared image; MSE; COUPLED NEURAL-NETWORKS; DESIGN;
D O I：
10.12785/amis/080638
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
To segment the infrared insulator image efficiently, an improved Unit-linking PCNN algorithm, which makes improvements on both the linking coefficient beta and the standard for choosing the best segmented image, is proposed in this paper. The relationship of the gray value of each neuron is used to determine the linking coefficient beta and MSE, which consider the relationship between the gray value of the original image and the segmented image, is used to determine the best segmented image. The proposed algorithm is tested on both the standard test images and the aerial infrared images and the results show that the proposed algorithm gives better segmentation of the target image and better vision effect and less time are needed to get the best one.
引用
收藏
页码：2997 / 3004
页数：8
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