计算机与数字工程2025，Vol.53Issue(3)：851-856,6.DOI:10.3969/j.issn.1672-9722.2025.03.040
一种改进Canny算法在肺炎图像边缘检测中的研究与应用
Research and Application of an Improved Canny Algorithm in Pneumonia Image Edge Detection
摘要
Abstract
In the process of diagnosis and treatment,patients with COVID-19 are judged by doctors on the lesions of lung X-rays,and doctors give diagnosis results based on professional knowledge and experience.In order to ensure that doctors give cor-rect and reliable diagnosis results during the diagnosis process,providing lung image pictures with clear edges and high sig-nal-to-noise ratio is a key step in the diagnosis and treatment of new coronary pneumonia patients.At present,the method of using the Canny edge detection algorithm combined with deep learning to realize the COVID-19 X-ray image detection method has good detection effect,but the generalization ability is poor and the diagnosis efficiency is low.Aiming at the problem that Gaussian filter-ing in the traditional Canny algorithm cannot eliminate the salt and pepper noise,and the adaptability of manual selection of high and low thresholds is insufficient,an improved Canny algorithm is proposed,and the contrast-limited adaptive histogram equaliza-tion(CLAHE)is first used to enhance the picture of the detected image.Secondly,the preprocessing of bilateral filtering is carried out,and since the selection of thresholds requires human intervention,the maximum between-class variance method is used to real-ize adaptive selection of high and low thresholds.Through comparative experiments,it is found that the improved algorithm performs better than the traditional Canny detection method,which can detect more edge details,more obvious contours,and improve image quality by 7%～15%.The advantages of Canny's algorithm with strong adaptability and strong ability to remove interference are main-tained.关键词
边缘检测/新冠肺炎/双边滤波/最大类间方差法Key words
edge detection/COVID-19/bilateral filtering/maximum interclass variance method分类
信息技术与安全科学引用本文复制引用
王煜,朱硕,吕宗奎..一种改进Canny算法在肺炎图像边缘检测中的研究与应用[J].计算机与数字工程,2025,53(3):851-856,6.基金项目
江苏省双创人才计划双创博士(编号:JSSCBS20210871) （编号:JSSCBS20210871）
无锡学院人才启动资金(编号:2021r014)资助. （编号:2021r014）
