娄联堂 何慧玲 石胜平.基于局部处理的X射线图像裂纹缺陷自动检测[J].中南民族大学学报自然科学版,2020,39(1):98-102
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
  
DOI:10.12130/znmdzk.20200118
中文关键词: 裂纹缺陷自动检测  感兴趣区域  局部增强  阈值分割  形态学处理
英文关键词: crack defect automatic detection  region of interest  local enhancement  threshold segmentation  morphological processing
基金项目:国家自然科学基金资助项目(60975011);中南民族大学中央高校基本科研业务费专项资金资助项目(CZW1501;YZZ13003)
作者单位
娄联堂 何慧玲 石胜平 1 中南民族大学 数学与统计学学院武汉4300742 中车长江车辆有限公司武汉430212 
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中文摘要:
      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.
英文摘要:
      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.
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