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PCNN模型在彩色图像分割中的应用 被引量：3

A segmentation method of color images based on improved PCNN
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摘要 针对脉冲耦合神经网络(PCNN)模型主要应用于灰度图像处理的局限性,利用脉冲发生器将颜色信息引入模型作为输入,与灰度信息共同控制神经元的内部行为,控制等灰度值的不同颜色区域分期点火,实现彩色图像的精确分割.双输入PCNN模型实现了彩色图像的分割,同时保持了PCNN模型对噪声的鲁棒性,从简单的仿真图像和实际图像两方面验证了此分割方法的有效性. To overcome the limitation of the pulse-coupled neural network （PCNN） for its application in processing of color images, the hue data were introduced into the basic PCNN model by adopting the signal generator to control the internal activities of cells. The pixels with the same grey level and different hue data were pulsed separately in the double-input PCNN. It is indicated that the double-input PCNN can achieve the segmentation of color images and is robust to noises. The experimental results on synthetic images and natural images verify the validity of the model.
作者 程丹松 刘晓芳 金野 魏子尧 唐降龙 刘家锋
机构地区 哈尔滨工业大学计算机科学与技术学院 哈尔滨工业大学电气工程学院 北京航空航天大学计算机系
出处 《哈尔滨工业大学学报》 EI CAS CSCD 北大核心 2009年第3期58-62,共5页 Journal of Harbin Institute of Technology
基金 哈尔滨青年科技创新人才基金资助项目(2008RFQXS037)
关键词 脉冲耦合神经网络(PCNN) 图像分割 彩色图像 pulse-coupled neural network （PCNN） image segmentation color image
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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共引文献193

同被引文献44

  • 1鲍晴峰,王继成.基于PCNN的彩色图像分割新方法[J].计算机工程与应用,2005,41(27):48-50. 被引量：19
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哈尔滨工业大学学报
2009年 第3期

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