基于图像分割原理，对检测图像中的缺陷区域进行分割和提取，根据超声波B型图像在纵向和横向的不同特点，改进了传统区域生长的图像分割方法；以超声波B型图像中的颜色极值点为种子像素，在图像的纵向和横向采用不同的生长准则，提出了在纵向上采用波谷阈值的生长准则，在横向上采用相关系数阈值的生长准则，并通过实际的铁路车轮超声波B型检测试验验证，取得了良好的缺陷信号区域分割效果。

In the ultrasonic B-scan inspection for railway wheels, defection region is to be isolated from the B-scan image on the basis of image segmentation. According to the deferent features of B-scan image at vertical and horizontal directions, a new method is introduced in this paper to solve the B-scan image segmentation as a result of improving the traditional region growing method. In the new method, the pixels with maximal color value are picked out as the seed pixels, and then different growing principles are used in the region growing method at vertical and horizontal directions, in which the principle of wave valley threshold is used at the vertical direction, and the principle of correlation coefficient threshold is used at the horizontal direction. By the experiments of ultrasonic B-san for railway wheels, it shows that the new region growing method behaves well and acquires a satisfied result of defection region segmentation.