基于Hausdorff距离区域生长的缺陷边缘重建方法

针对X射线探伤图像中的缺陷被提取时易产生形变,提出一种基于Hausdorff距离区域生长的缺陷边缘重建方法.首先对图像求补运算,以分水岭算法决定结构元素尺寸,采用改进的自适应数学形态学滤波算法处理图像,图像经阈值分割得到包含缺陷的二值图像;在此基础上对缺陷目标进行形态学收缩得到区域生长的若干种子点,以种子点的原始像素值为初始值,选择目标区域中的像素值大于或等于初始值的像素点进行合并生长得到新目标图像,以初始值减去2得到新的初始值,然后循环生长并计算新目标Canny边缘图像与原目标Canny边缘图像的Hausdorff距离,采用最小hausdorff距离为区域生长停止规则,所有目标生长完全后经过组合从而实现缺陷边缘重建.试验结果表明,该方法能够有效恢复缺陷的原貌,缺陷边缘重建效果明显.

METHOD OF DEFECT EDGE RECONSTRUCTION BASED ON REGION GROWING ALGORITHM AND THE HAUSDORFF DISTANCE

Aiming to edge deformation in extracting the de- fects of X-ray weld images, a method of defect edge recon- struction based on region growing and the Hausdorff distance is proposed. Firstly, the complement of the image is computed and the size of structure is chosen by watershed algorithm. Then, the image is filtered by improved adaptive morphology filter and its two valued image comprised of the defects is obtained. On this basis, the seeds are obtained by shrinking the objects to points. The original gray value of seeds serve as the beginning value and the object region grows by combining these selected pixels whose gray values are greater than or equal to the begin- ning value which is renewed by 2 subtracted from the previous. Then, the object region grows iteratively and the Hausdorff distance of the Canny edge image of objects and the original objects are calculated each time. The region growing stop when the minimum Hausdorff distance is achieved. When all objectsregion growing are completed, the defect edge is reconstructed by region growing. The method is verified by experiments and the results prove that the method is avail to renew the original shape of defect and obtain good results in defect edge recon- struction.