针对线结构光三维形貌测量中大量噪声易干扰激光条纹中心提取准确度的问题, 提出了一种条纹亚像素中心提取方法。分析条纹图像中的噪声, 采用平均法和中值滤波预处理图像; 利用迭代阈值分割及形态学方法, 获取条纹目标, 引入距离变换提取条纹的像素级中心; 根据像素级中心、二值信息及光强灰度, 结合曲线拟合及重心法精确提取条纹的亚像素中心。仿真分析和实验验证下, 相邻行条纹中心列坐标最大偏差值像素小于2 , 平均偏差像素值约为0.3, 与传统方法相比, 2项指标值更小。实验结果表明, 算法有效利用条纹灰度分布规律, 可降低噪声对中心定位精度的影响, 更逼近条纹真实中心位置, 抗噪能力极强。

Aiming at the problem that the extraction accuracy of laser stripe center can be easily disturbed by a large amount of noise in line structured light 3D shape measurement, a method for extracting the stripe sub-pixel center was proposed. First, the noise in the stripe image was analyzed and preprocessed by the average method and median filtering. Then, the stripe was obtained by iterative threshold segmentation and morphological method, and the pixel center was extracted by distance transform. Finally, on the basis of the pixel center, binary information and light intensity, the precise sub-pixel center of the stripe was extracted by combining curve fitting with barycenter method. After simulation analysis and experimental verification, the maximum value and average value of column coordinate deviation between adjacent rows of stripe center are about 2 pixels and 0.3 pixels, respectively, smaller than the traditional method. Experimental results show that, the algorithm based on the effective use of the stripe gray distribution, can effectively reduce the influence of noise, approach to the true center of stripe more cosely, with extremely strong noise proof ability.