机械制造与自动化2024，Vol.53Issue(3)：66-69,118,5.DOI:10.19344/j.cnki.issn1671-5276.2024.03.014
基于机器视觉的镍板材表面缺陷检测研究
Nickel Plate Surface Defect Detection Base on Machine Vision
摘要
Abstract
To handle the quality defects on the surface of nickel sheet,a defect detection method combining adaptive fractional differentiation and improved Canny algorithm is proposed.Bilateral filtering is used to denoise and preserve the edge of the image.A gradient-enhancing mask is designed and integrated into Sobel to form a double-layer convolution kernel,enhancing defect edges gradient and weakening the gradient inside the defect and in the background area.The watershed algorithm is applied to replace the non-maximum suppression and the morphological edge connection algorithm for edge refinement.The experimental results show that the detection effect of the proposed algorithm on nickel plate defects is better than the classical algorithm and some other improved algorithms.关键词
机器视觉/表面缺陷检测/改进Canny/最大熵Key words
machine vision/surface defect detection/improved Canny/maximum entropy分类
信息技术与安全科学引用本文复制引用
李建华,刘广鹏,赵正天,雷春丽..基于机器视觉的镍板材表面缺陷检测研究[J].机械制造与自动化,2024,53(3):66-69,118,5.基金项目
国家重点研发计划项目(2020YFB1713600) （2020YFB1713600）
