| 一种改进的PCNN图像分割算法 |
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| 引用本文： | 宋寅卯,刘国乐.一种改进的PCNN图像分割算法[J].电路与系统学报,2010,15(1). |
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| 作者姓名： | 宋寅卯 刘国乐 |
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| 作者单位： | 郑州轻工业学院,电气信息工程学院,河南,郑州,450002 |
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| 摘 要： | PCNN用于图像分割时,为获得满意分割效果,其参数往往通过反复试凑确定,这在一定程度上限制了PCNN的使用。为此在改进的PCNN基础上,提出结合图像灰度直方图,以最大交叉熵函数作自适应遗传算法的适应度函数,采用自适应遗传算法搜索最优门限阈值的图像分割算法。该方法可有效地完成图像分割,分割结果优于原PCNN和传统Ostu算法。
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| 关 键 词： | PCNN 自适应遗传算法 最大交叉熵 图像分割 |
An image segmentation algorithm based on an improved PCNN |
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| SONG Yin-mao,LIU Guo-le.An image segmentation algorithm based on an improved PCNN[J].Journal of Circuits and Systems,2010,15(1). |
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| Authors: | SONG Yin-mao LIU Guo-le |
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| Affiliation: | College of Electrical and Information Engineering;Zhengzhou University of Light Industry;Zhengzhou 450002;China |
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| Abstract: | PCNN is very suitable for image segmentation. However, it is necessary to determine the adaptive parameters of the network to achieve satisfactory segmentation results for different images. Up to now, the parameters of PCNN are always adjusted manually, which impedes its application in image segmentation. Aiming at the difficulties and shortcomings with using PCNN in image segmentation, combining the gray histogram of images, using the maximal cross-entropy function as the fitness function of Adaptive Genet... |
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| Keywords: | PCNN adaptive genetic algorithm maximal cross-entrop image segmentation |
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