Li Yuehua, Zhou Jingbo, Huang Fengshan, Liu Lijian
School of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China.
Sensors (Basel). 2017 Apr 10;17(4):814. doi: 10.3390/s17040814.
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.
激光条纹中心提取是线结构光传感器（LSLS）轮廓测量的关键步骤。为了在亚像素级别准确获取中心坐标，提出了一种改进的灰度重心法（IGGM）。首先，使用灰度重心法（GGM）计算图像所有列的条纹中心点。通过使用移动最小二乘算法拟合这些点，可以稳健地获得切线向量、法线向量和曲率半径。可以围绕每个中心点定义一个矩形区域。其与切线向量平行的两条边可以根据曲率半径改变长度。之后，在矩形区域内并沿法线向量方向重新计算每个中心点的坐标。还基于蒙特卡罗方法分析了中心不确定性。获得的实验结果表明，IGGM适用于光滑条纹和有尖角的条纹。可以以相对较低的计算成本获得高精度的中心点。楼梯和螺旋面的测量结果进一步证明了该方法的有效性。
