基于改进ORB-RANSAC算法的锅底标签角度视觉测量方法

Angle visual measurement method of pot bottom label based on improved ORB-RANSAC algorithm

传统ORB-RANSAC算法存在相似特征点误匹配率高、稳定性较差的问题,无法满足铝锅生产基于锅底标签方向焊接手柄的工艺要求,提出了一种改进的ORB-RANSAC算法。首先,采用ORB算法提取特征点并进行匹配,通过汉明距离阈值法对匹配点对进行粗剔除。其次,在RANSAC算法对匹配点对进行精剔除时,增加K折交叉验证实现对初始模型的一致性预判断。最后,在每次迭代过程中剔除上一轮迭代中的已归类点对,动态更新采样空间。分别对不同锅底标签进行测量实验,结果表明,在干扰环境下采用改进后的ORB-RANSAC算法重复性精度相比于原算法提升了66.04%,单帧计算耗时降低了6.13%;在多种类锅底标签测量实验中基于改进后的ORB-RANSAC算法的角度测量误差为0.201°,平均检测耗时为0.255 s,满足自动化生产测量精度和实时性的要求。

The traditional ORB-RANSAC algorithm has the problems of high error matching rate and poor stability of similar feature points,which can not meet the technological requirements of welding handle based on the direction of bottom label in aluminum pot production.An improved ORB-RANSAC algorithm is proposed.Firstly,ORB algorithm was used to extract and match the feature points,and hamming distance threshold method was used to remove the matching points.Secondly,when RANSAC algorithm performs fine elimination of matching point pairs,k-fold cross-validation is added to achieve consistency prejudgment of the initial model.Finally,the classified point pairs in the previous iteration are removed during each iteration,and the sampling space is dynamically updated.The results show that the repeatability accuracy of the improved ORB-RANSAC algorithm is improved by 66.04%compared with the original algorithm in the interference environment,and the single frame calculation time is reduced by 6.13%.The Angle measurement error based on the improved ORB-RANSAC algorithm is 0.201°and the average detection time is 0.255sin the multi-type pot bottom label measurement experiment,which meets the requirements of automatic production measurement accuracy and real-time.