An Image Segmentation Method Using Image Enhancement and PCNN with Adaptive Parameters
2012 ◽
Vol 490-495
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pp. 1251-1255
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Keyword(s):
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.
1988 ◽
Vol 02
(02)
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pp. 301-319
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2014 ◽
Vol 998-999
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pp. 925-928
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2014 ◽
Vol 687-691
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pp. 3616-3619
2013 ◽
Vol 860-863
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pp. 2783-2786
2014 ◽
Vol 602-605
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pp. 2199-2204
2012 ◽
Vol 263-266
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pp. 2082-2087
2012 ◽
Vol 155-156
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pp. 861-866
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2013 ◽
Vol 380-384
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pp. 1189-1192
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2013 ◽
Vol 860-863
◽
pp. 2888-2891