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基于改进Sobel算子的边缘检测算法的研究
引用本文:何春华,张雪飞,胡迎春.基于改进Sobel算子的边缘检测算法的研究[J].光学技术,2012,38(3):323-327.
作者姓名:何春华  张雪飞  胡迎春
作者单位:广西工学院计算机工程系;桂林电子科技大学光机电一体化研究所;广西工学院发展规划处
基金项目:广西科学研究与技术开发计划项目(桂科攻0815003-6)
摘    要:针对传统Sobel边缘检测算法对噪声敏感的缺点进行了分析,提出了自适应权值的改进算法,该权值的大小取决于Sobel算子模板内像素灰度值之和。通过不同形式的噪声图像处理对比,结果表明,该算法不仅计算简单,而且具有较强的抗噪能力,对图像边缘有较高的检验精度,极大地改进了图像边缘识别的效果。

关 键 词:边缘检测  自适应权值  改进Sobel算子  Sobel算子模板
收稿时间:2011/11/3

A study on the improved algorithm for Sobel on image edge detection
HE Chunhua,ZHANG Xuefei,HU Yingchun.A study on the improved algorithm for Sobel on image edge detection[J].Optical Technique,2012,38(3):323-327.
Authors:HE Chunhua  ZHANG Xuefei  HU Yingchun
Institution:1.Department of Computer Engineering,Guangxi University of Technology,Liuzhou 545006,Guangxi,China)(2.The Institute of OPTO-Mechatronics,Guilin University of Electronic Technology,Guilin 541004,Guangxi,China)(3.Development Planning Office,Guangxi University of Technology,Liuzhou 545006,Guangxi,China)
Abstract:In view of the traditional Sobel algorithm for edge detection is sensitive to noise,an improved Sobel algorithm of adaptive weights is proposed.The weights depend on the sum of pixel gray value within the template of the Sobel operator.In comparison of processing different noise images,the results show that the improved Sobel algorithm is not only in high calculation efficiency,but also with a strong anti-noise ability.It is proved that the improved Sobel algorithm has higher precision and it is much more effective in edge recognition.
Keywords:edge detection  adaptive weights  improved Sobel algorithm  Sobel operator template
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