Mean shift算法在带钢缺陷图像分割中的应用

Application of the Mean shift algorithm in steel strip image segmentation

带钢自动表面检测系统中缺陷图像的分割效果对缺陷识别具有重要影响.为了提高缺陷图像的分割效果,提出了采用Mean shift算法对带钢缺陷图像中的感兴趣区域进行平滑从而获取缺陷边缘的方法,并将该算法与中值滤波算法进行了比较.测试结果表明,Mean shift算法能够有效地对缺陷图像中的感兴趣区域进行平滑,并精确得到缺陷目标的边缘,该算法在带钢的缺陷分割中具有较好的性能.

Defect segmentation results affect the precision of classification in the automatic strip surface defect detection system. In order to obtain a better result, the mean shift algorithm is presented to segment the defects in strip images. The mean shift algorithm is used to smooth the region of interest in the image and detect the defecCs edge, and its effectiveness is compared with that of the median filter. Test results show that it can smooth strip images effectively and can detect the edges of defect objects accurately. The mean shift algorithm can work effectively in strip image segmentation.