Research on Adhesive Workpiece Recognition and Positioning Based on Machine Vision

Zhengbo Wang, Xing Ma, C. Mu, Haiping An
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引用次数: 3

Abstract

For solving the problem of identification and location of scattered and adhesive workpieces, this paper studies on multi-object workpieces in the background of robot workbench with machine vision technology: Firstly, to segment the adhesive workpieces and extract them, the identification processing is based on the improved SURF(speeded up robust features)+BOW(visual word bag)+SVM(support vector machine). Finally, using depth sensor Kinect to locate the workpiece. Workpiece with different shapes are tested, results show that the system can segment the adhesive workpiece better, and achieve the extraction of multi-target workpiece, while the positioning error is less than 5mm.
基于机器视觉的粘接工件识别与定位研究
为了解决散乱粘接工件的识别与定位问题,本文采用机器视觉技术对机器人工作台背景下的多目标工件进行了研究:首先,对粘接工件进行分割和提取,基于改进的SURF(加速鲁棒特征)+BOW(视觉词袋)+SVM(支持向量机)进行识别处理;最后,利用Kinect深度传感器对工件进行定位。对不同形状的工件进行了测试,结果表明,该系统能较好地对粘接工件进行分割,实现了多目标工件的提取,定位误差小于5mm。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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