射线检测底片缺陷图像的预处理技术  

Image preprocessing technology for defects of radiographic testing film

作　　者：罗颖 张义凤 蒋建生 LUO Ying;ZHANG Yifeng;JIANG Jiansheng(Shanghai Research Institute of Materials Co.,Ltd.,Shanghai 200437,China;School of Engergy and Materials,Shanghai Second University of Technology,Shanghai 201209,China;Shanghai Key Laboratory of Engineering Materials Application and Evaluation,Shanghai 200437,China)

机构地区：[1]上海材料研究所有限公司,上海200437 [2]上海第二工业大学能源与材料学院,上海201209 [3]上海市工程材料应用与评价重点实验室,上海200437

出　　处：《无损检测》2024年第2期22-28,共7页Nondestructive Testing

基　　金：基于数字射线的腐蚀沉积物检测标准与自动识别研究(20DZ2203800)。

摘　　要：图像识别技术是人工智能在焊缝射线检测技术领域的典型应用场景之一,开展图像识别技术在工业焊缝检测和智能监测中的研究和应用,对推动无损检测智能化发展具有重要意义。射线检测底片缺陷图像预处理能够在短时间内将复杂图片简单化,为后续的缺陷识别打好基础。X射线检测原始图像灰度区间窄,对比度低,噪声大,为解决这一问题,采用不同的降噪处理与对比度增强图片预处理方法,开展了射线检测底片预处理试验,并根据实际检测效果优化了参数,改进了算法。试验结果表明,降噪方面,中值高斯组合滤波的降噪效果较好;对比度增强方面,线性变换的对比度增强效果较好。Image recognition technology is one of the typical application scenarios of artificial intelligence in the field of weld seam radiographic testing.Conducting research and application of image recognition technology in industrial weld seam detection and intelligent monitoring is of great significance for promoting the intelligent development of non⁃destructive testing.The preprocessing of defect images in radiographic testing can simplify complex images in a short period of time,laying a solid foundation for subsequent defect recognition.Due to the narrow gray range,low contrast,and high noise in the original X⁃ray detection image,different denoising and contrast enhancement image preprocessing methods were used to solve this problem.X⁃ray film preprocessing experiments were conducted,and parameters were optimized and algorithms were improved based on actual detection results.The experimental results showed that in terms of noise reduction,the median Gaussian combination filter had a better noise reduction effect;In terms of contrast enhancement,linear transformation had a better effect on contrast enhancement.

关 键 词：图像预处理 缺陷识别 射线检测 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TG115.28[自动化与计算机技术—计算机科学与技术]