Robust Printing Defect Detection on 3D Textured Surfaces by Multiple Paired Pixel Consistency of Orientation Codes

被引:0
作者
Xiang, Sheng [1 ]
Yan, Yaping [1 ]
Asano, Hirokazu [2 ]
Kaneko, Shun'ichi [1 ]
机构
[1] Hokkaido Univ, Grad Sch Informat Sci & Technol, Sapporo, Hokkaido 0600814, Japan
[2] Huawei Technol Japan KK, Yokohama, Kanagawa 2210056, Japan
来源
PROCEEDINGS 2018 12TH FRANCE-JAPAN AND 10TH EUROPE-ASIA CONGRESS ON MECHATRONICS | 2018年
关键词
defect detection; multiple paired pixel consistency; orientation code; 3D textured surface;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A new method for defect detection in 3D textured (SHIBO) surface is proposed. In the presence of 3D textured surfaces, and/or illumination change such as shadowing or highlighting, many conventional ways for visual inspection have been proved as of some troubles. For such purposes, it is proposed to utilize the orientation code based consistence of multiple pixel pairs to detect defects on character which is printed on 3D textured surface. This algorithm consists of two stages, they are training stage and detecting stage. Training stage is for making defect-free model based on multiple paired pixel consistency. Detecting stage is to identify whether the target pixel match its model. Experimental results for real products image demonstrate the effectiveness of the proposed method for defect inspection and location.
引用
收藏
页码:373 / 378
页数:6
相关论文
共 14 条
  • [1] [Anonymous], 2008, ELCVIA ELECT LETT CO
  • [2] Fucheng Y., 2009, MECH AUT 2009 ICMA 2
  • [3] Fast connected-component labeling
    He, Lifeng
    Chao, Yuyan
    Suzuki, Kenji
    Wu, Kesheng
    [J]. PATTERN RECOGNITION, 2009, 42 (09) : 1977 - 1987
  • [4] Hoseini Elham, 2013, International Journal of Computer Theory and Engineering, V5, P114, DOI 10.7763/IJCTE.2013.V5.658
  • [5] Texture representation using Autoregressive models
    Joshi, Mangala S.
    Bartakke, Prashant P.
    Sutaone, M. S.
    [J]. 2009 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTATIONAL TOOLS FOR ENGINEERING APPLICATIONS, 2009, : 386 - +
  • [6] Mahmoudi F., 2012, INT J SOFT COMPUT EN, V2, P2231
  • [7] Print registration for automated visual inspection of transparent pharmaceutical capsules
    Mehle, Andraz
    Bukovec, Marko
    Likar, Bostjan
    Tomazevic, Dejan
    [J]. MACHINE VISION AND APPLICATIONS, 2016, 27 (07) : 1087 - 1102
  • [8] Narendra V. G., 2011, International Journal of Agricultural and Biological Engineering, V4, P83, DOI 10.3965/j.issn.1934-6344.2011.02.083-090
  • [9] Automated fabric defect detection-A review
    Ngan, Henry Y. T.
    Pang, Grantham K. H.
    Yung, Nelson H. C.
    [J]. IMAGE AND VISION COMPUTING, 2011, 29 (07) : 442 - 458
  • [10] Detection of surface defects on raw steel blocks using Bayesian network classifiers
    Pernkopf, F
    [J]. PATTERN ANALYSIS AND APPLICATIONS, 2004, 7 (03) : 333 - 342