激光与光电子学进展, 2019, 56 (9): 091501, 网络出版: 2019-07-05   

基于机器视觉的包装袋缺陷检测算法研究与应用 下载: 1532次

Machine-Vision Based Defect Detection Algorithm for Packaging Bags
作者单位
沈阳城市建设学院信息与控制工程系, 辽宁 沈阳 110167
摘要
提出了一种基于机器视觉的包装袋缺陷检测方法。以冰棍包装袋缺陷检测为实例,提取了长度、宽度、面积、填充度和监测框与内部目标区域的位置关系5种特征值,经缺陷检测与分类,输出了连袋、外形尺寸错误、包装袋上有异物和包装版面移动4种缺陷类型。实验结果表明,算法缺陷识别成功率可达98.75%,满足生产过程对实时、快速、高精度的要求,已被应用于实际生产线,取得了良好效果。
Abstract
A machine-vision based defect detection method for packaging bags is proposed. Considering the defect detection of ice-lolly bags as an example, five kinds of eigenvalues of length, width, area, filling degree, and location relationship between the monitoring frame and the internal target region are extracted. After defect detection and classification, the following four types of defects are outputted: continuous bags, dimension errors, foreign matters on packages, and motion of packaging layout. The experimental results demonstrate that the recognition success rate of the proposed algorithm can reach 98.75%, which meets the requirements of high speed, high precision, and real time in the production process. The algorithm has been applied to an actual production line and has achieved good results.

李丹, 白国君, 金媛媛, 童艳. 基于机器视觉的包装袋缺陷检测算法研究与应用[J]. 激光与光电子学进展, 2019, 56(9): 091501. Dan Li, Guojun Bai, Yuanyuan Jin, Yan Tong. Machine-Vision Based Defect Detection Algorithm for Packaging Bags[J]. Laser & Optoelectronics Progress, 2019, 56(9): 091501.

本文已被 6 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!