南京理工大学学报（自然科学版）2018，Vol.42Issue(2)：177-182,6.DOI:10.14177/j.cnki.32-1397n.2018.42.02.007
一种引导滤波自适应双阈值优化边缘检测算法
Adaptive double threshold modified edge detection algorithm for boot filtering
摘要
Abstract
The edge detection is one of the important aspects of image processing. The traditional edge detection method includes two kinds of methods,the method based on the template matching and the method based on the image gradient. In order to overcome the shortages that the template matching method losses more edge information and the image gradient method is easily affected by the noise,an adaptive double threshold modified Kirsch edge detection algorithm is proposed for the boot filtering. For the local information feature of the image,the boot filtering function is dynamically generated at different edge positions of the image to maintain and enhance the edge effect. At the same time,the complex computation of the Kirsch operator is simplified,and the two thresholds are adaptively selected according to the image edge region threshold.The combination of the two thresholds can effectively improve the accuracy and the efficiency of the edge detection algorithm. The experi-mental results show that,compared with the traditional Kirsch algorithm and the Sobel algorithm,the improved algorithm is better in the edge localization and operation speed,and the processing speed of the image is more than 4 times of the traditional's while the fine real edge is well detected.关键词
引导滤波/自适应双阈值/边缘检测Key words
boot filtering/adaptive double threshold/edge detection分类
信息技术与安全科学引用本文复制引用
许乐灵,胡石..一种引导滤波自适应双阈值优化边缘检测算法[J].南京理工大学学报（自然科学版）,2018,42(2):177-182,6.基金项目
安徽省高等学校自然科学重点研究项目(KJ2018A0181) （KJ2018A0181）
安徽省高等学校质量工程重点研究项目(2016jyxm0715) （2016jyxm0715）
安徽省高校优秀青年人才支持计划项目(gxyq2017218) （gxyq2017218）
