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CCD机器视觉在缺陷检测中的关键技术研究 被引量:1

Research on Key Techniques of CCD Machine Vision in Defect Detection
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摘要 随着人工智能和机器视觉技术的发展,利用机器视觉技术对精密工件表面的缺陷检测也就成为了必然。采用计算机视觉技术和人工智能的方法将会极大地提高检测精度和效率。本课题主要研究基于CCD工业相机的机器视觉技术在精密机械缺陷检测中的关键技术,期望能够实现利用计算机来对精密机械的缺陷进行高质量的自动检测。 With the development of artificial intelligence and machine vision technology,the precision of workpiece surface defect detection based on machine vision technology has become a necessity.The method will computer vision technology and artificial intelligence to improve the detection accuracy and efficiency.This paper mainly studies the key technology of machine vision technology CCD industrial camera in the detection precision mechanical defects based on the expected design to realize automatic detection using the computer to carry out high quality defects of precision machinery.
作者 钱礼闰 QIAN Li-run(Department of Automotive Engineering,Anhui Vocational College of Defense Technology,Lu'an,Anhui 237011,China)
出处 《教育教学论坛》 2018年第15期58-59,共2页 Education And Teaching Forum
基金 安徽省2014年高校自然科学研究重点项目(编号:KJ2017A781)(项目名称:悬臂式大量程精密轮廓测量仪关键技术研究) 2015年院级质量工程项目(编号:gf2015MOOC06)
关键词 机器视觉 特征提取 缺陷检测 分类器 machine vision feature extraction defect detection classifier
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  • 1李军,马瑞伍,刘杰.注射成型制品常见缺陷及处理方法[J].模具工业,2006,32(3):61-64. 被引量:16
  • 2BARTLEET,TREVOR C.Real time machine vision inspection of plastic bottle closures[J].The International Society for Optical Enzineerinz,1995,2598(35):362-370.
  • 3LIU BIN,WU SHENGJIN.Automatic detection technology of surface defects on plastic products based on machine vision[C].2010 International Conference on Mechanic Automation and Control Engineering,2010: 2213-2216.
  • 4Iivarinen J. Surface defect detection with histogram-based texture features[A].Washington,DC:SPIE,2000.140-145.
  • 5Xie X H. A review of recent advances in surface defect detection using texture analysis techniques[J].Electronics Letters on Computer Vision and Image Analysis,2008,(03):1-22.
  • 6Monadjemi A. Towards efficient texture classification and abnormality detection[D].Bristol:University of Bristol.Faculty of Engineering,Department of Computer Science,2004.13-28.
  • 7Truchetet F,Laligant O. Review of industrial applieations of wavelet and multiresolution-based signal and image processing[J].Journal of Electronic Imaging,2008,(03):1-11.
  • 8Tsai D,Hsiao B. Automatic surface inspection using wavelet reconstruction[J].Pattern Recognition,2001.1285-1305.
  • 9Choi M,Kim R Y,Nam M R. Fusion of multispectral and panchromatic satellite images using the curvelet transform[J].IEEE Transactions on Geoscience and Remote Sensing,2005,(02):136-140.
  • 10Le P E,Mallat S. Sparse geometric image representation with bandelets[J].IEEE Transactions on Image Processing,2005,(04):423-438.

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