一种简化PCNN模型在彩色图像边缘检测上的应用

doi:10.3969/j.issn.1001-2400.2012.06.001

Abstract

Abstract:

An improved color image edge detection method is proposed to overcome the defects of miss-detection and false-detection in traditional methods which are caused by thinking little of chroma information and the influence of noise. This paper exploits the color principal axis to represent both the luminance and the chroma information so that the color image can be converted into a pseudo gray image where color information is contained. Besides, we apply the Pulse Coupled Neural Networks (PCNN) model to reduce the influence of noise. Since we expect fewer arguments in the PCNN model to make our adjusting easier, a simplified version of PCNN is used to solve this problem. Experiment proves that this method which takes advantage of both PCNN model and color principal axis method can help us obtain the exact edge of the color image while the bad influence of noise is significantly suppressed.

Key words: edge detection, image processing, color principal axis, pulse coupled neural networks (PCNN) algorithm

CLC Number:

TN911.73

SHAO Xiaopeng;ZHONG Cheng;WANG Yang;HUANG Yuanhui. Application of a simplified PCNN model in color image edge detection[J].J4, 2012, 39(6): 1-9.

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Application of a simplified PCNN model in color image edge detection

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