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Sub-Pixel Extraction of Laser Stripe Center Using an Improved Gray-Gravity Method

机译:改进的灰度重力法亚像素提取激光条纹中心

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摘要

Laser stripe center extraction is a key step for the profile measurement of line structured light sensors (LSLS). To accurately obtain the center coordinates at sub-pixel level, an improved gray-gravity method (IGGM) was proposed. Firstly, the center points of the stripe were computed using the gray-gravity method (GGM) for all columns of the image. By fitting these points using the moving least squares algorithm, the tangential vector, the normal vector and the radius of curvature can be robustly obtained. One rectangular region could be defined around each of the center points. Its two sides that are parallel to the tangential vector could alter their lengths according to the radius of the curvature. After that, the coordinate for each center point was recalculated within the rectangular region and in the direction of the normal vector. The center uncertainty was also analyzed based on the Monte Carlo method. The obtained experimental results indicate that the IGGM is suitable for both the smooth stripes and the ones with sharp corners. The high accuracy center points can be obtained at a relatively low computation cost. The measured results of the stairs and the screw surface further demonstrate the effectiveness of the method.
机译:激光条纹中心提取是测量线结构光传感器(LSLS)轮廓的关键步骤。为了准确获得亚像素级的中心坐标,提出了一种改进的灰度重力法(IGGM)。首先,对于图像的所有列,使用灰度重力法(GGM)计算条纹的中心点。通过使用移动最小二乘算法拟合这些点,可以可靠地获得切向矢量,法向矢量和曲率半径。可以在每个中心点周围定义一个矩形区域。它的平行于切向矢量的两侧可以根据曲率半径更改其长度。之后,在矩形区域内并沿着法线向量的方向重新计算每个中心点的坐标。还基于蒙特卡洛方法分析了中心不确定性。实验结果表明,IGGM既适用于光滑的条纹,也适用于尖角的条纹。可以以较低的计算成本获得高精度的中心点。楼梯和螺钉表面的测量结果进一步证明了该方法的有效性。

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