Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (21): 214-216.

• 图形、图像、模式识别 • Previous Articles     Next Articles

Research on improved morphology and wavelet transform algorithm for edge detection

YAO Yufeng,XIA Kaijian,ZHONG Shan,CHANG Jinyi   

  1. College of Computer Science and Engineering,Changshu Institute of Technology,Changshu,Jiangsu 215500,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-07-21 Published:2011-07-21

改进的形态学和小波变换边缘检测算法研究

姚宇峰,夏开建,钟 珊,常晋义   

  1. 常熟理工学院 计算机科学与工程学院,江苏 常熟 215500

Abstract: An improved edge detecting algorithm based on mathematical morphology and wavelet transform is proposed to overcome the limitation which embarrasses the performance of the traditional mathematical morphological methods.In the low-frequency image,the coefficients that have maximal absolute values are selected and the consistency of these coefficients is verified,while the high-frequency sub-image edges are detected by multi-scales and two-structuring elements mathematical morphology.Finally it can get a complete edge of the image.Experimental results show that compared with the traditional wavelet transform edge detecting method and math morphology method,this method can adaptively extract accurate edge information,and better decrease the noise.

Key words: wavelet transform, math morphology, edge detection, multi-structuring elements, noise

摘要: 针对传统数学形态学边缘检测算法存在的图像噪声干扰、边缘分辨率较低等问题,提出了一种基于数学形态学与小波变换方法相结合的边缘检测改进算法。在小波域中,对图像分解的弱边缘进行适当的加强,对低频系数采用模极大值法进行边缘处理,对边缘细节比较多的高频系数采用基于多尺度的双结构元素数学形态学算法进行边缘检测,最终得到图像的完整边缘。实验结果表明与传统的小波变换边缘检测法以及数学形态学边缘检测等方法相比,此种算法更能有效提取准确的边缘信息,而且又具有很强的抗噪性,是一种有效的边缘检测方法。

关键词: 小波变换, 数学形态学, 边缘检测, 多结构元素, 噪声