成捆圆钢机器人贴标系统图像识别方法

黄风山; 秦亚敏; 任玉松

doi:doi:10.3969/j.issn.1003-501x.2016.12.026

光电工程, 2016, 43 (12): 168, 网络出版: 2016-12-30

成捆圆钢机器人贴标系统图像识别方法

The Image Recognition Method on Round Bales Robot Labeling System

论文大纲

黄风山 ^*秦亚敏任玉松

作者单位

河北科技大学机械工程学院，石家庄 050018

摘要

为实现成捆圆钢端面自动化及高效率贴标，建立了成捆圆钢机器人贴标系统。本文重点对复杂背景下圆钢端面图像识别进行研究，提出了一种圆钢端面图像组合识别方法。首先确定圆钢半径范围，利用分水岭分割算法对粘连图像进行分割，为防止因过分割而造成圆钢端面图像的漏识、错识，提出了真圆度阈值和角度阈值组合算法，以实现对分割后圆钢端面图像的准确识别。然后用椭圆拟合法确定圆钢端面图像中心点像素坐标，通过Delaunay 三角剖分内插值法标定完成像素坐标到世界坐标的转换，最后组建了成捆圆钢端面贴标试验系统。结果表明：成捆圆钢机器人贴标系统贴标速度为20 根/min，贴标准确率高达99.8%。能满足企业实际生产需求，为国内外成捆圆钢端面自动化贴标技术的发展和实际应用提供了一定参考。

Abstract

In order to realize the automation and high efficiency labeling of round bales, a robot labeling system of round bales has been constructed. A image recognition method of round bale end face under complex background has been studied and a combined recognition algorithm is proposed. Firstly, the radius range of round bale is determined, and the watershed algorithm is used to segment the adhesion image. In order to prevent the leakage and error identification of round bale end face caused by over-segmentation, true roundness threshold and angle threshold are proposed to recognize the over-segmented images further precisely. Then the pixel coordinate centers of round bale end faces are obtained using the ellipse fitting method, and the conversion relationship between the pixel coordinates and world coordinates is completed by the calibration based on the Interpolation of Delaunay Triangles. Finally, the labeling experimental system is set up. Experimental results show that the speed of this labeling system is 20 roots per minute,and the accuracy rate is 99.8%. The system can meet the actual production needs of enterprises, and it can provide certain reference for technology development and practical application of round bale end face automatic labeling at home and abroad.

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黄风山, 秦亚敏, 任玉松. 成捆圆钢机器人贴标系统图像识别方法[J]. 光电工程, 2016, 43(12): 168. HUANG Fengshan, QIN Yamin, REN Yusong. The Image Recognition Method on Round Bales Robot Labeling System[J]. Opto-Electronic Engineering, 2016, 43(12): 168.

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