摘要
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 characteris- tics 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.
出处
《中国图象图形学报》
CSCD
北大核心
2012年第9期1122-1127,共6页
Journal of Image and Graphics
基金
国家自然科学基金项目(60870007)
关键词
轮对检测
图像分割
区域生长
单连接区域生长
wheel set measurement
image segmentation
region growing
single connected region growing
