文档介绍：毕业设计(论文)
题目:图像边缘检测方法研究
英文题目:Research on Image Edge Detection Methods
学生姓名肖龙
学号 07323116
指导教师李国萍职称讲师
专业信息工程
二零一一年六月
摘要
数字图像边缘检测是图像分割、目标区域识别和区域形状提取等图像分析领域十分重要的基础,,这些信息可以用于图像理解和分析,,目前它已成为机器视觉研究领域最活跃的课题之一,在工程应用中占有十分重要的地位.
经典的边缘检测方法如:Roberts,Sobel,Prewitt,Kirsch,Laplaee等方法,基本上都是对原始图像中像素的小邻域构造边缘检测算子,进行一阶微分或二阶微分运算,求得梯度最大值或二阶导数的过零点,、不能自适应选择闭值、检测效果不太理想等缺点.
本文对边缘检测理论和算法作了深入的研究,在具体分析各类传统的边缘检测算法的基础上,重点研究了Canny算法,,用MATLAB 实现该算法,实验结果表明,改进后的算法(CMO算法)取得比传统的Canny算法更好的边缘检测效果.
关键词:图像处理; 边缘检测; Canny算子; 滤波; 自适应阈值
ABSTRACT
Digital image edge detection plays an import part in image analysis, such as image segmentation, interested region recognition and region shape it’s an import method in image feature extraction of image edge includes the valuable infotmation of the image which can be use in image understanding and through edge detection,we can greatly reduce the calculation of image analysis and processing in the following ,the first step of image understanding and analysis is edge detection,and it has been the most active topic in the machine vision research field,also it plays an import part in engineering application.
Most of the traditional edge detection algorithms,such as Roberts,Sobel,Prewitt, Kirsch,Laplacian ,just construct an edge detection algorithm with a small neighborhood in each pixel of the original image,and then carry out with first differential or second differential operator in order to obtain the maximum gradient or the zero-crossing point of the second derivative,finally select an appropriate threshold to extract the these algorithms share the same ings,for example,they are sensitive to noise,they can’t select threshold adaptively,and the detection results are not so well.
In this paper,we do a deep research on the edge det