一种基于Canny的自适应图像边缘提取方法  

Self-adaptive image edge detection method based on Canny

作　　者：黄剑玲[1] 熊艰[1] 邹腾博[2] 

机构地区：[1]上饶师范学院数学与计算机科学学院,江西上饶334000 [2]华北电力大学电力系,河北保定071000

出　　处：《计算机工程与应用》2011年第34期219-221,234,共4页Computer Engineering and Applications

基　　金：江西省教育厅科学技术研究项目(No.GJJ11608)

摘　　要：针对传统Canny算子需要人为指定高斯滤波参数和高低阈值的问题,提出一种自适应方法,采用基于非下采样Contourlet变换的自适应阈值去噪算法代替高斯滤波对图像去噪,同时保持图像的边缘信息,然后采用最大类间方差的方法进行高低阈值的自适应设定,并用此高低阈值对经过非极大值抑制后的图像进行检测及连接边缘。理论和实验结果表明,与传统Canny算子相比,该算法在滤除图像噪声、保留细节边缘方面获得了不错的效果,并且提高了边缘的自动化检测能力。In order to fix the inconvenience that in traditional Canny operator,human intervention is required to select the Gaussian filter parameter and the high and low threshold,this paper proposes a self-adaptive edge detection method. Instead of applying Gaussian filter,this method uses self-adaptive thresholding algorithm,which is based on Nonsubsampled Contourlet Transform（NSCT） algorithm,to denoise an image and keep its edge information.Then the Otsu method sets high and low thresholds automatically,which are applied to edge detection and connection of the image generated by non-maximal suppression.The theoretical and experimental results show that this method,compared with the traditional Canny operator,not only filters out image noises and keeps detail edges efficiently,but also improves its automation.

关 键 词：非下采样CONTOURLET变换 最大类间方差 自适应方法 CANNY算子 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]