轮对作为列车的重要组成部分,其踏面磨耗参数的在线检测对保障轨道交通安全具有重要意义。在基于光截图像测量技术的轮对外形尺寸动态检测中,能否获取完整的轮对轮廓图像至关重要。针对轮对图像特点,提出一种基于区域生长的轮对图像分割新算法。该算法根据不同情况下轮对图像特点,通过基点位置选取恰当的种子点,并确定合适的生长准则。经过区域生长,有效地提取轮对轮廓图像。通过大量图像验证,该算法分割结果图的交迭面积比大于80%,误分面积比小于0.02%。可以在多种情况下有效地提取轮对轮廓曲线,具有良好的抗噪能力。

The wheel set is the major running component of a train. Online measurement of wheel set wear parameters is important for train safety. Acquiring a completely structured light projection image is important to wheel set profile dynamic inspection method.We develop a new image segmentation algorithm based on region growing. According to the characteristics of wheel set images acquired in different conditions and the location of their base points, a new growth standard of the algorithm is proposed. The wheel set profile images are extracted effectively through proper seed selection and growth process. By processing a series of images with severe noise and external disturbances, the overlap area ratio is more than 80%, and the error segmentation area ratio is less than 0.02%. The wheel set profile curves can be extracted effectively based on the new algorithm.