板料成形过程中劈裂缺陷在线检测的机器视觉系统

F. Gayubo, Jose Luis Navarro Gonzalez, Eusebio de la Fuente López, F. M. Trespaderne, J. Perán
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引用次数: 28

摘要

在本文中,我们设计了一个用于检测板料成形过程中是否存在劈裂缺陷的自动系统。图像采集系统基本上包括一个CCD渐进相机和一个安装在六自由度机器人末端执行器上的漫射照明系统。检测机器人将图像采集系统置于从钣金成形线出发的工件上。识别、定位和后期检测是在工件在传送带上移动的过程中实现的。为了实现检测,利用马尔科夫随机场模型对采集到的图像进行恢复。缺陷检测采用谷检测算法。为了实现识别和确定精确的位置,我们使用了基于主成分分析(PCA)的基于外观的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On-line machine vision system for detect split defects in sheet-metal forming processes
In this paper, we present an automatic system designed for detect the presence of split defects in sheet-metal forming processes. The image acquisition system includes basically a CCD progressive camera and a diffuse illumination system mounted on the end-effector of a 6-dof robot. The inspection-robot displaces the image acquisition system over the pieces proceeding from the sheet-metal forming line. The recognition, positioning and the later inspection are realized as the pieces are moving on a conveyor belt. To realize the inspection, the acquired images are restored using a Markov random field model. Defect detection is carried out using a valley detection algorithm. To realize the recognition and to determine the precise position, we have used an appearance-based method, based on a principal component analysis (PCA)
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