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Received:May 23, 2020 Revised:June 16, 2020
Received:May 23, 2020 Revised:June 16, 2020
中文摘要: 针对多孔材料在生产工艺中易出现阻塞和缺角等缺陷, 本文设计了一种基于机器视觉的多孔材料表面缺陷检测方法, 通过对目标区域的有效分割、模糊度检测、形态学处理和分析等技术手段, 实现了该类材料的表面缺陷的快速定位和特征分析. 经实验检测, 本文算法的准确性和检测效率可以满足工业生产实时检测需求.
Abstract:Aiming at the defects of porous materials such as blockage and angle gap, a method of surface defect detection for porous materials based on machine vision is designed in this study. By means of effective segmentation of target area, ambiguity detection, morphological treatment and analysis, the rapid location and feature analysis of surface defect for porous materials are realized. The experimental results show that the accuracy and efficiency of the algorithm can meet the real-time detection requirements of industrial production.
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基金项目:国家自然科学基金面上项目(11772301); 浙江省自然科学基金(LY17F020016); 工业智能制造项目(杭州师范大学第二轮专业学位研究生课程教学案例库建设)
引用文本：
金顺楠,周迪斌,朱江萍.基于机器视觉的多孔材料缺陷检测.计算机系统应用,2021,30(1):270-276
JIN Shun-Nan,ZHOU Di-Bin,ZHU Jiang-Ping.Defect Detection of Porous Materials Based on Machine Vision.COMPUTER SYSTEMS APPLICATIONS,2021,30(1):270-276
金顺楠,周迪斌,朱江萍.基于机器视觉的多孔材料缺陷检测.计算机系统应用,2021,30(1):270-276
JIN Shun-Nan,ZHOU Di-Bin,ZHU Jiang-Ping.Defect Detection of Porous Materials Based on Machine Vision.COMPUTER SYSTEMS APPLICATIONS,2021,30(1):270-276
