基于PCNN的灰度图像边缘检测方法  

Gray Image Edge Detection Method Based on PCNN

作　　者：杨智勇[1] 周琪云[1] 周定康[1] 

机构地区：[1]江西师范大学计算机应用研究所,南昌330027

出　　处：《计算机工程与应用》2004年第21期92-93,107,共3页Computer Engineering and Applications

摘　　要：脉冲耦合神经网络(PCNN)最初由Eckhorn根据猫大脑中视觉皮层神经元的同步脉冲(SynchronousBurst)现象而提出。由于具有一系列良好的特性,PCNN在图像处理、模式识别等领域获得了广泛的应用。文献[6]根据PCNN的传播特性提出了一种利用PCNN检测二值图像边缘的有效方法,但这种方法并不能直接用于对灰度图像的边缘进行检测。由于实际处理的图像大部分为灰度图像,因而其方法的适用性是很有限的。该文提出了一种基于PCNN的灰度图像边缘检测方法,从而直接对256色灰度图像的边缘进行提取,具有较好的适用性。实验结果表明该方法是有效的。The PCNN was originally presented to explain the synchronous burst of the neurons in the cat visual cortex by Eckhorn.For its good properties,it is widely used in image processing and pattern recognition.In reference,an effective method for binary image edge detection based on PCNN is proposed.But the method can not detect edges in gray image directly.Since most of practical images that need to be processed are gray image,the applicability of the method is limited.This paper proposes a method based on PCNN to detect edges in a gray image.This method can detect edges in a256colors gray image directly and is applicable.Experiment results show that the method is effective.

关 键 词：PCNN 灰度图像边缘检测 图像处理 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]