电子测量与仪器学报

彭永志,肖靖,毛建旭,代扬,张猛.一种基于 DBSCAN 随机圆检测的多瓶口定位算法[J].电子测量与仪器学报,2021,35(6):43-52

一种基于 DBSCAN 随机圆检测的多瓶口定位算法

Multi bottle mouth positioning methodbased on DBSCAN random circle detection

DOI：

英文关键词:clustering DBSCAN algorithm circle detection multi bottle mouth positioning

基金项目:国家自然科学基金(61733004，62027810）、国家重点研发计划项目(2020YFB1712600）、湖南省科技计划项目（2017XK2102，2018GK2022）、湖南大学汽车车身先进设计制造国家重点实验室自主研究课题资助

作者	单位
彭永志	1.湖南大学电气与信息工程学院
肖靖	1.湖南大学电气与信息工程学院
毛建旭	1.湖南大学电气与信息工程学院
代扬	1.湖南大学电气与信息工程学院
张猛	1.湖南大学电气与信息工程学院

Author	Institution
Peng Yongzhi	1.College of Electrical and Information Engineering, Hunan University
Xiao Jing	1.College of Electrical and Information Engineering, Hunan University
Mao Jianxu	1.College of Electrical and Information Engineering, Hunan University
Dai Yang	1.College of Electrical and Information Engineering, Hunan University
Zhang Meng	1.College of Electrical and Information Engineering, Hunan University

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中文摘要:

现有医药灌封生产中的西林瓶瓶口定位方法易受瓶口边缘干扰的影响,导致瓶口圆中心定位不准确。对此,提出一种基于 DBSCAN 随机圆检测的多瓶口定位算法。首先,通过 Canny 边缘检测算法得到图像中所有轮廓,采用基于密度的 DBSCAN 聚类算法分割出感兴趣的瓶口边缘集;接着,针对每个单独的瓶口边缘集,采用最小二乘法和径向扫描获取瓶口的外边缘点,再利用重复随机圆检测得到大量候选圆心集;最后,基于 DBSCAN 算法聚类得到真实圆心集,以真实圆心集的均值中心作为瓶口中心。与 4 种典型算法进行对比,实验结果表明,提出的圆定位算法的平均定位误差为 0. 553 pixels,优于其他算法,且该算法的平均执行速度为 1. 359 ms。该算法能够满足医药灌封生产线对准确性和实时性的要求。

英文摘要:

In pharmaceutical encapsulation production, the existing positioning method of Penicillin bottle mouth are easily affected by the interference of bottle mouth edge. It leads to inaccurate positioning of the bottle mouth circle center. In this paper, a multi bottle mouth positioning algorithm based on DBSCAN random circle detection is proposed. Firstly, the canny edge detection algorithm is used to get all the contours in the image. The density based on DBSCAN clustering algorithm is used to segment the interested bottle mouth edge sets. Then, for each individual bottle mouth edge image, the least square method and radial scanning are used to obtain the outer edge points of the bottle mouth. Then, a large number of candidate center sets are obtained by repeated random circle detection. Finally, the truth is obtained by clustering based on DBSCAN algorithm. The mean center of the real circle center set is the center of the bottle mouth. Compared with four typical algorithms, the experimental results show that the average positioning error of the proposed circle positioning algorithm is 0. 553 pixels, which is better than other algorithms. And the average execution speed of the algorithm is 1. 359 ms. The algorithm meets the requirements of accuracy and real-time of the pharmaceutical potting production line.

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