The PCNN adaptive segmentation algorithm based on visual perception

被引:1
作者
Zhao, Yanming [1 ]
机构
[1] Hebei Normal Univ Nationalities, Dept Math & Comp, Chengde 067000, Peoples R China
来源
PIAGENG 2013: IMAGE PROCESSING AND PHOTONICS FOR AGRICULTURAL ENGINEERING | 2013年 / 8761卷
关键词
Image segmentation; pulse coupled neural network; Gabor; visual perception information; region connectivity; adaptive parameter determination;
D O I
10.1117/12.2020133
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
To solve network adaptive parameter determination problem of the pulse coupled neural network (PCNN), and improve the image segmentation results in image segmentation. The PCNN adaptive segmentation algorithm based on visual perception of information is proposed. Based on the image information of visual perception and Gabor mathematical model of Optic nerve cells receptive field, the algorithm determines adaptively the receptive field of each pixel of the image. And determines adaptively the network parameters W, M, and beta of PCNN by the Gabor mathematical model, which can overcome the problem of traditional PCNN parameter determination in the field of image segmentation. Experimental results show that the proposed algorithm can improve the region connectivity and edge regularity of segmentation image. And also show the PCNN of visual perception information for segmentation image of advantage.
引用
收藏
页数:6
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