融入一维概率Hough变换与局部Zernike矩的双目视觉测量  

Binocular vision measurement method incorporating one-dimensional probabilistic Hough transform and local Zernike moment

作　　者：张浩 许四祥[1] 董晨晨 周书华 ZHANG Hao;XU Sixiang;DONG Chenchen;ZHOU Shuhua(College of Mechanical Engineering,Anhui University of Technology,Ma'anshan 243032,China)

机构地区：[1]安徽工业大学机械工程学院,安徽马鞍山243032

出　　处：《光学精密工程》2023年第12期1793-1803,共11页Optics and Precision Engineering

基　　金：国家自然科学基金资助项目(No.51374007);安徽高校自然科学研究重点资助项目(No.KJ2020A0259);特种重载机器人安徽重点实验室开放基金资助项目(No.TZJQR005-2021)。

摘　　要：针对被测物体理想角点不易检测致使测量精度不高的问题,提出一种融入一维概率Hough变换与局部Zernike矩的双目视觉测量方法。首先利用一维概率Hough变换对物体外轮廓边缘进行直线检测;然后根据直线检测结果建立感兴趣区域,在各局部区域内利用Zernike矩进行亚像素检测,并在两相邻感兴趣区域的相交范围内完成亚像素点筛选;之后通过正交总体最小二乘法进行亚像素边缘直线拟合,并进行关键点匹配;最后利用三角测量原理获得被测物体的三维空间信息完成测量。以连铸坯模型为测量对象,实验结果表明:此算法最小相对误差达到0.3401%,满足测量要求。长度相对误差均值为0.3945%,与传统SIFT,ORB算法相比分别降低80.01%和74.63%;与其他边缘拟合算法相比测量误差减小34.11%,运行时间缩短39.07%,验证了此算法的精确性和高效性。To address the low measurement accuracy resulting from the inability to detect ideal corners of an object,a binocular-vision-based measurement method incorporating the one-dimensional probabilistic Hough transform and local Zernike moment is proposed herein.First,the one-dimensional probabilistic Hough transform is used for line detection of the outer contour.Next,sub-pixel extraction is performed using the Zernike moment method in the region of interest(ROI)established according to the line detection,and sub-pixel points are screened in the intersection region of the ROI.Then,before matching the key points,sub-pixel edge lines are fitted using the orthogonal total least squares method.Finally,the three-dimensional spatial information of a continuous casting slab model is obtained via the triangulation principle,and the measurement is completed.Here,the continuous casting slab model is considered as the measurement object.Experimental results indicate that the minimum relative error of the proposed algorithm is 0.3401%,which satisfies the measurement requirement.The average relative error in the length is 0.3945%,which is 80.01%and 74.63%smaller than those of the traditional SIFT and ORB algorithms,respectively.Compared with another method based on edge fitting,the measurement error and time consumption of the proposed algorithm are reduced by 34.11%and 39.07%,respectively,confirming its measurement accuracy and efficiency.

关 键 词：双目视觉 一维概率Hough变换 亚像素 边缘拟合 测量 

分 类 号：TP394.41[自动化与计算机技术—计算机应用技术]