Computer Engineering and Applications ›› 2017, Vol. 53 ›› Issue (9): 190-194.DOI: 10.3778/j.issn.1002-8331.1510-0223

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Fusion of double threshold and improved morphological edge detection

CUI Liqun, ZHANG Yue, TIAN Xin   

  1. School of Software, Liaoning Technical University, Huludao, Liaoning 125105, China
  • Online:2017-05-01 Published:2017-05-15


崔丽群,张  月,田  鑫   

  1. 辽宁工程技术大学 软件学院,辽宁 葫芦岛 125105

Abstract: The key to image edge detection is to suppress noises more effectively while detecting as much as possible the edges of image. For this purpose, this paper proposes a fusion dual-threshold and mathematical morphology edge detection method. First of all, the source image is decomposed by wavelet decomposition, it uses dual-threshold method for high frequency components of treatment, and uses multi-structure element algorithm for multi-scale mathematical morphology frequency components for low frequency component. And then the level of sub-subtraction method is used for image fusion edge. The experimental results show that the algorithm is superior to wavelet modulus maxima algorithm or mathematical morphological method and can more effectively suppress noise. The edges are consecutive and clear.

Key words: edge detection, double threshold, mathematical morphology, image fusion

摘要: 图像边缘检测的关键是在尽量多检测到边缘的同时更有效地抑制噪声,为此提出一种融合双阈值和数学形态学的边缘检测方法。首先对原图像进行小波分解,利用双阈值法处理高频分量,利用多尺度多结构数学形态学算法处理低频分量;然后采用差影法对高低频边缘图像融合。实验结果表明,对比单一使用小波模极大值法或数学形态学法,该算法具有更好的抑制噪声能力,检测出的边缘更加连续、清晰。

关键词: 边缘检测, 双阈值, 数学形态学, 图像融合