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平顶线结构光的中心检测算法及光刀平面标定

Center Detection Algorithm and Knife Plane Calibration of Flat Top Line Structured Light

张旭   周涛  
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摘要

针对传统线结构光光刀平面标定方法测量精度不高, 应用范围小的问题, 提出基于平面标靶的线结构光系统光刀平面标定, 对无激光的标靶图片进行迭代摄像机标定, 有激光的标靶图片进行光刀平面标定.提出光强符合均匀分布的平顶激光检测中心算法, 将平顶激光建模为矩形的台阶函数, 估计背景亮度和前景亮度, 确定亮条纹宽度, 再将窗口内的有效像素参与重心计算, 得到光条纹中心.用该算法对不同噪声及不同量块的图片进行处理, 结果表明, 处理后图像的均方根误差分别在0.149 pixel和0.176 pixel内, 表明该算法抗噪声能力强、精度高.用该算法提取光条中心, 计算光条在标靶上的位置, 根据至少两个姿态下的光条中心三维点, 基于最小二乘法拟合光刀平面.通过迭代摄像机标定和光刀平面标定, 利用三角测量法, 在立体视觉模型下获取物体的三维点云数据.实验测量两个距离为100.5 mm的标准球, 相机与标准球距离为500 mm, 比较两球心距离与标准距离, 测得平均误差为0.236 mm.表明平顶激光检测中心算法切实可行, 光刀平面标定方法基本满足要求.

Abstract

Aiming at the problem that the traditional line structured light plane calibration measurement accuracy is not high and the range of applications is small, a light knife plane calibration method of structured light system based on plane target was proposed. The iterative camera calibration was performed for target image without laser, and the light knife plane calibration was performed for laser target picture. The flat top laser detection center algorithm was proposed that made the light intensity coincide with the uniform distribution. The flat top laser was modeled as a rectangular step function, then the brightness of the background and foreground brightness were estimated to determine light stripe width, and then the light stripe centerge was obtained by calculating the center of gravity within the window of effective pixels. The algorithm was used to deal with pictures with different noise and different blocks, the results show that the root mean square errors are within 0.149 pixel and 0.176 pixel, respectively, which means that the algorithm has high anti-noise ability and high precision. The light strip center was extracted by using the proposed algorithm, the position of the light bar on the target was calculated. According to the light strip center 3D points of at least two postures, the light knife plane was fitted by least squares. By means of iterative camera calibration and knife plane calibration, 3D point cloud data was obtained in the stereo vision model by using triangulation. Two standard balls with mutual distance of 100.5mm were experimental measured, the distance between the camera and the standard balls is 500mm, the distance between two ball centers and the standard distance were compared, the measured average error is 0.236mm. It shows that the flat top laser detection center algorithm is practicable, and the method of light knife plane calibration basically meets the requirements.

Newport宣传-MKS新实验室计划
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中图分类号:TP391

DOI:10.3788/gzxb20174605.0512001

基金项目:国家自然科学基金(Nos.51575332, 61673252)和国家重点研发计划子课题(No.2016YFC0302401)资助

收稿日期:2016-11-08

修改稿日期:2017-01-24

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作者单位    点击查看

张旭:上海大学 机电工程与自动化学院, 上海 200072机械系统与振动国家重点实验室, 上海 200240
周涛:上海大学 机电工程与自动化学院, 上海 200072

联系人作者:张旭(xuzhang@shu.edu.cn)

备注:张旭(1982-), 男, 副教授,博士,主要研究方向为深度信息获取、计算机视觉、图像处理等.

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引用该论文

ZHANG Xu,ZHOU Tao. Center Detection Algorithm and Knife Plane Calibration of Flat Top Line Structured Light[J]. ACTA PHOTONICA SINICA, 2017, 46(5): 0512001

张旭,周涛. 平顶线结构光的中心检测算法及光刀平面标定[J]. 光子学报, 2017, 46(5): 0512001

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