| 周荣富,赵光宇,蒋仕龙,陈方涵.基于二值条纹动态照明的透明平滑曲面缺陷识别[J].光电子激光,2020,31(4):372~379 |
| 基于二值条纹动态照明的透明平滑曲面缺陷识别 |
| Defects recognition of curved smooth transparent surface exploiting dynamic bina ry fringe lighting |
| 投稿时间：2019-11-08 |
| DOI： |
| 中文关键词: 透明曲面 表面异常 条纹投影 动态照明 缺陷检测 |
| 英文关键词:curved transparent surface surface abnormality fringe projection dynamic ligh ting defects inspection |
| 基金项目:国家自然科学基金(U1613209)、2018国家重点研发计划专项资金(2018YFB1308604)和深圳市技术攻关科技研发资金 (JSGG20190220164202211) (1.攀枝花学院智能制造学院,攀枝花 617000; 2.华南师范大学 华南先进光电子研究院 光及电磁波研究中心,广州 510006； 3.北京大学深圳研究院运动控制技术实验室,深圳 518057) |
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| 中文摘要: |
| 针对在透明光滑表面视觉检测中,商用照明系统 较难获取高对比度曲面瑕疵特征的局限性,论文提出了基于二 值条纹的动态背向照明方法。该照明投影出一组等间距位移量的动态二值条纹图案,将亮暗 条纹之间的过度区覆盖至整 个待测表面,最大化缺陷与光滑表面的透射光线方向性差异。对动态条纹照明后的透明曲面 序列图像均值处理后,获取 均一背景下的缺陷特征图像。之后结合小波变换边缘提取与直方图全局阈值分割的方法,极 大增强了光滑曲面与平面上的外观缺陷信息。基于3D曲面手机玻璃的测试结果表明,该方法 成功提取出透明光滑曲面上的低对比度缺陷,为缺陷的准确识别提供了可靠保障,具有良好的应用前景。 |
| 英文摘要: |
| High contrast feature of flaws on curved smooth transparent surface wa s hard to be captured by available commercial lighting systems.In consideration of the limitation of illumination for surface inspection,a back-light system exploiting dynamic binary fringe was presented.The lighting projected a set of dynamic binary fringes with equal interval movement,which contributed the transition zone between bright and dark stripe t o cover the entire surface detected, and maximized the directional difference between light rays transmitted respecti vely by defect and flawless surface. The feature of defect with homogenous background could be obtained by averaging the curved transparent image sequences illuminated by dynamic binary fringe.Combined with edge extraction ba sed on wavelet transform and global threshold segmentation based on histogram distribution,the appearance de fects on both curved and flat surface were greatly improved.The test results of three dimensional curved mobile glass demonstrated that the method mentioned abo ve could successfully extract low contrast defects on transparent curved surface ,provide a reliable guarantee to recognize defects accurately,and has a good app lication prospect. |
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