为了实时检测钢轨焊缝边缘错边量合格情况，提出了基于计算机视觉的钢轨焊缝自动定位方法.首先，采用中值滤波对焊缝图像进行噪声去除；其次，采用限制对比度自适应直方图均衡算法和直方图均衡化法进行焊缝图像增强；然后，采用双阈值OTSU法进行图像分割，突出轨头和焊缝区域图像，并采用连通域法提取轨头和焊缝区域轮廓；最后，采用多次最小二乘直线拟合法获取焊缝拟合直线，计算拟合直线与轨头上边缘直线的交点作为定位点，实现钢轨焊缝自动定位.对60 kg/m钢轨焊缝区域的检测实验表明，所提方法具有精度高、稳定性好的优点，可用于焊轨基地焊缝的在线实时自动检测.
In order to detect the edge misalignment of rail weld in real time, an automatic positioning method for the rail weld based on computer vision is proposed. First, the method of median filtering is used to remove the noise in a weld image. Second, the weld image is enhanced by using the contrast limited adaptive histogram equalization (CLAHE) algorithm and the histogram equalization method. Third, the image is segmented by the double threshold OTSU method to highlight the rail head and the weld region, and the contours of the rail head and the weld region are extracted by using the method of connected-domain. Finally, the weld fitting line is obtained by multiple least squares fitting, and the intersection of the fitted straight line and the top edge line of the rail head are calculated as the positioning point, accordingly, the rail weld is automatic positioned. Through a test of the weld region of 60 kg/m rail, the method performs with high precision and stability, and can be used for measuring the rail weld automatically in real-time on line.
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