期刊文献+

基于图像处理技术的树脂镜片瑕疵分类特征研究 被引量:5

Resin lens defect classification based on image processing
原文传递
导出
摘要 在基于机器视觉技术的镜片自动检测系统中,为了实现镜片的分级,需要对镜片瑕疵进行分类。利用建立的图像获取系统自动检测树脂镜片瑕疵;针对镜片点杂质、划痕和羽毛3种瑕疵的分类问题,提出了以圆形度、直线拟合相关系数作为分类特征的方法,通过数据统计计算出分类特征的阈值,并分析了细化算法对划痕和羽毛直线拟合相关系数的影响,结果表明,细化算法对于提高划痕和羽毛的分类准确率具有重要作用。实验验证了算法的可行性,并分析了误判的原因。实验结果表明,3种瑕疵的分类准确率为96%。 During the lens automatic detection ba sed on machine vision technology,the defects should be classified in order to ac hieve the grading of the lenses.Automatic detection system components, working principle and the resin lens major defects are simply introduced.As for the classification of the three main defects of point impurities,scratches and feathers,the circularity and straight-line fitting correlation have been propos ed in this paper as the classifying features.The threshold of the classifying features has been calculated on the basis of data analysis and statistics.The i nfluence of the thinning algorithm on the straight-line fitting correlation has been discussed for the defects of scratches and feathers.The experimental results show that the thinning algorithm plays an imp ortant role in improving classification accuracy of scratches and feathers.The experiment is conducted to analyze the feasibility of the algorithm.The results indicate that this method has a high c lassification accuracy of 96% for the three defects,which meets the requiremen ts of the detection system.
出处 《光电子.激光》 EI CAS CSCD 北大核心 2014年第2期330-335,共6页 Journal of Optoelectronics·Laser
基金 江苏丹阳市应用技术研究计划(12142K)资助项目
关键词 图像处理 瑕疵分类 圆形度 直线拟合 image processing defect classification circularity straight-line fitting
作者简介 E-mail:yaoye@ujs.edu.cn姚红兵(1976-),男,江苏省泰兴市人,博士,副教授,硕士生导师,主要从事光电检测和激光技术及应用方面的研究.
  • 相关文献

参考文献12

二级参考文献126

共引文献183

同被引文献58

  • 1李本伍,王小华,谢君廷.一种图像中检测直线的快速算法[J].杭州电子科技大学学报(自然科学版),2007,27(6):67-70. 被引量:8
  • 2张晓,杨国光,程上彝,左丹微.光学表面疵病的激光频谱分析法及其自动检测仪[J].仪器仪表学报,1994,15(4):396-399. 被引量:10
  • 3戴名奎,徐德衍.光学元件的疵病检验与研究现状[J].光学仪器,1996,18(3):33-36. 被引量:30
  • 4张萍,朱政红.机器视觉技术及其在机械制造自动化中的应用[J].合肥工业大学学报(自然科学版),2007,30(10):1292-1295. 被引量:40
  • 5Maropoulos P,Muelaner J,Summers M,et al.A new paradigm in large-scale assembly—research priorities in measurement assisted assembly[J].The Interna tional Journal of Advanced Manufacturing Technology,2014,70(1-4):621-633.
  • 6Brosnan T,SUN D-W.Improving quality inspection of food p roducts by computer vision—a review[J].Journal of Food Engineering,2004,61(1):3-16.
  • 7Mapayi T, Viriri S, Tapamo J R.Adaptive thresholding techniq ue for retinal vessel segmentation based on GLCM-energy information[J].Comput Math Method M,2015,2015(1):1-11.
  • 8Qi X,Xiao R,Li C,et al.Pairwise rotation inva riant Co-occurrence local binary pattern[J].Pattern Analysis and Machine Int elligence,IEEE Transactions on,2014,36(11):2199-2213.
  • 9Gui W,Liu J,Yang C,et al.Color co-occurrence ma trix based froth image texture extraction for mineral flotation[J].Minerals Engineering,2013,46- 47(1):60-67.
  • 10Jeon J,Cho S,Tong X,et al.Intrinsic image dec omposition using structure-texture separation and surface normals[M].Computer Vision-Eccv 2014,Pt Vii.2014,218-233.

引证文献5

二级引证文献21

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部