An Image Segmentation Method Using Image Enhancement and PCNN with Adaptive Parameters

被引：2

作者：

Cai, Hong ^{[1
]}

Zhang, Xueyuan ^{[1
]}

Dai, Haitao ^{[1
]}

Zhou, Dongming ^{[1
]}

机构：

[1] Yunnan Univ, Informat Coll, Kunming 650091, Peoples R China

来源：

MECHATRONICS AND INTELLIGENT MATERIALS II, PTS 1-6 | 2012年 / 490-495卷

关键词：

PCNN; Enhancement algorithm; Adaptive parameters; Image segmentation;

D O I：

10.4028/www.scientific.net/AMR.490-495.1251

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

PCNN model is particularly suitable for image segmentation and edge extraction, but its effect depends on the selection of parameters in PCNN model and network iteration settings, which needs for a large number of artificial interaction and has limited PCNN image processing practicality. In this paper, through combining statistical properties of images and PCNN model, we present an adaptive algorithm based on the distribution of pixels to replace the artificial interaction. Experimental results show that image segmentation using image enhancement and PCNN with adaptive parameters is significantly better than the traditional PCNN image segmentation and verify the effectiveness of the method.

引用

页码：1251 / 1255

页数：5

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