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

Hong Cai; Xue Yuan Zhang; Hai Tao Dai; Dong Ming Zhou

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

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 490-495An Image Segmentation Method Using Image...

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

Abstract:

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.

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Periodical:

Advanced Materials Research (Volumes 490-495)

Pages:

1251-1255

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.490-495.1251

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Online since:

March 2012

Authors:

Hong Cai, Xue Yuan Zhang, Hai Tao Dai, Dong Ming Zhou

Keywords:

Adaptive Parameters, Enhancement Algorithm, Image Segmentation, PCNN

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