基于局部处理的X射线图像裂纹缺陷自动检测

Automatic detection of crack defects in X-ray image based on local processing

研究了X射线图像裂纹缺陷自动检测问题.首先根据裂纹缺陷特征及位置信息提取感兴趣区域,使检测到的缺陷区域准确地包含实际缺陷;然后提出了一种结合局部方差和局部直方图均衡化的图像增强方法,实现了图像的对比度增强,使裂纹缺陷肉眼可见;接着利用阈值分割和形态学方法对裂纹缺陷进行分割提取;最后根据裂纹缺陷的几何特征实现了裂纹缺陷的检测.实验结果表明:相比于仅利用局部方差或局部直方图均衡化对图像做一次对比度增强,此方法能有效增强缺陷特征,更利于缺陷检测.

The problem of automatic detection of crack defects in X-ray images is studied. Firstly, the region of interest is extracted according to the feature and location information of crack defects, so that the defect areas detected accurately contain the actual defects. Then, an image enhancement method combining local variance and local histogram equalization is proposed to enhance the contrast of the image and make the crack visible to the naked eye. Next, threshold segmentation and morphological analysis are used to segment and extract the crack defects. Finally, the detection of crack defects is realized according to the geometric characteristics of crack defects. The experiment results show that this method can effectively enhance the defect features and is more conducive to defect detection than only using local variance or local histogram equalization to enhance the image contrast once.