为保证钢轨磨损动态视觉测量的高精度, 综合图像获取和图像处理技术, 实现了清晰光条图像获取和光条中心点亚像素坐标精确提取。根据光条与背景环境亮度的高对比度, 提出一种依据光条亮度的相机自动曝光法, 用于获取清晰的光条图像; 分析图像光条法线方向的亮度衰变特征, 采用动态阈值分割法初步提取光条, 滤除图像背景的同时保留光条法线方向的亮度衰减信息; 根据图像过度曝光信息确定光条中心点像素大致位置, 再对分割的光条图像相对应像素位置点计算Hessian矩阵, 获取光条中心点的亚像素坐标。采用MFC编写应用程序进行试验, 在不同光照环境和背景物的干扰下, 该方法可精确地提取光条中心, 与经典Steger算法相比提取精度偏差为0.05 pixel, 运算时间节约40%。试验结果验证了该方法稳定性好, 有较强的抗干扰能力, 较好地满足钢轨磨损测量的现场要求。

In order to ensure the high precision of dynamic visual measurement of rail abrasion, image acquisition and image processing technology were used to get clear light-stripe image and extract the sub-pixel coordinates of the light-stripe accurately. First, according to the high contrast between the light-stripe and the background brightness, a method of automatic exposure of the camera based on the brightness of the light-stripe was proposed, which could ensure a clear image of the light-stripe. Then the dynamic threshold segmentation method was presented to extract the light-stripe preliminarily according to the lightness decay feature of the light-stripe in the normal direction, this method can filter out the background of the image while preserving the normal attenuation of light. Finally, according to the overexposure information of the image to determine the approximate position of the center point of the light-stripe, then the Hessian matrix was calculated for the corresponding pixel position of the segmented image to obtain the sub-pixel coordinates of the light-stripe. Using MFC to write application for testing, under different illumination and background interference, this method can accurately extract the center of light-stripe, the extraction accuracy is 0.05 pixel and the computation time is reduced by 40% compared with the classical Steger algorithm. Experimental results show that the proposed method has good stability and strong anti-interference ability, can meet the requirements of the rail abrasion measurement.