Design of inspection system of glaze defect on the surface of ceramic pot based on machine vision

被引:0
|
作者
Bao, Nengsheng [1 ]
Ran, Xie [1 ]
Wu, Zhanfu [1 ]
Xue, Yanfen [1 ]
Wang, Keyan [1 ]
机构
[1] Shantou Univ, Engn Coll, Shantou, Peoples R China
来源
PROCEEDINGS OF 2017 IEEE 2ND INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC) | 2017年
关键词
machine vision; ceramic pot; defect; online inspection;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Because of the restriction of glaze technology in the production of ceramic pot, it is easy to cause glaze defects on the surface. Currently, many ceramic pot production enterprises are still using artificial inspection of glaze defect on ceramic surface, which not only affects the ceramic pot production efficiency, but also cannot ensure the defect inspection accuracy. In terms of the current situation, an online inspection method of glaze on the surface of ceramic pot based on machine vision is proposed, so as to rapidly and accurately detect whether the target object has defects. This paper introduces the image processing algorithm of the common defects of ceramic pot, and establishes the online test platform. The experimental results show that the system can effectively glaze defects on the surface of ceramic pot products. This paper has some theoretical and applied value for the development of ceramic pot automatic detection technology.
引用
收藏
页码:1486 / 1492
页数:7
相关论文
共 50 条
  • [11] Defect Straw Inspection Method Based on Machine Vision
    Zhu, Ying
    Zhang, Hui
    Zhang, Zhisheng
    Xia, Zhijie
    2020 IEEE 3RD INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND SIGNAL PROCESSING (ICICSP 2020), 2020, : 198 - 202
  • [12] Machine vision system for curved surface inspection
    Lee, MFR
    de Silva, CW
    Croft, EA
    Wu, QMJ
    MACHINE VISION AND APPLICATIONS, 2000, 12 (04) : 177 - 188
  • [13] Machine vision system for curved surface inspection
    Min-Fan Ricky Lee
    Clarence W. de Silva
    Elizabeth A. Croft
    Q.M. Jonathan Wu
    Machine Vision and Applications, 2000, 12 : 177 - 188
  • [14] Design of Gear Defect Detection System Based on Machine Vision
    Wang, Yu
    Wu, Zhiheng
    Duan, Xianyun
    Tong, Jigang
    Li, Ping
    Chen, Min
    Lin, Qinglin
    2017 3RD INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND MATERIAL APPLICATION (ESMA2017), VOLS 1-4, 2018, 108
  • [15] Machine learning-based imaging system for surface defect inspection
    Je-Kang Park
    Bae-Keun Kwon
    Jun-Hyub Park
    Dong-Joong Kang
    International Journal of Precision Engineering and Manufacturing-Green Technology, 2016, 3 : 303 - 310
  • [16] Machine Learning-Based Imaging System for Surface Defect Inspection
    Park, Je-Kang
    Kwon, Bae-Keun
    Park, Jun-Hyub
    Kang, Dong-Joong
    INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY, 2016, 3 (03) : 303 - 310
  • [17] Simulation process for the design and optimization of a machine vision system for specular surface inspection
    Seulin, R
    Bonnot, N
    Merienne, F
    Gorria, P
    MACHINE VISION AND THREE-DIMENSIONAL IMAGING SYSTEMS FOR INSPECTION AND METROLOGY II, 2002, 4567 : 129 - 140
  • [18] ASPARAGUS DEFECT INSPECTION WITH MACHINE VISION
    RIGNEY, MP
    BRUSEWITZ, GH
    KRANZLER, GA
    TRANSACTIONS OF THE ASAE, 1992, 35 (06): : 1873 - 1878
  • [19] Vision-based Inspection System for Leather Surface Defect Detection and Classification
    Hoang-Quan Bong
    Quoc-Bao Truong
    Huu-Cuong Nguyen
    Minh-Triet Nguyen
    PROCEEDINGS OF 2018 5TH NAFOSTED CONFERENCE ON INFORMATION AND COMPUTER SCIENCE (NICS 2018), 2018, : 300 - 304
  • [20] Defect inspection system of nuclear fuel pellet end faces based on machine vision
    Zhang, Bin
    Liu, Mengmeng
    Tian, Yongzhi
    Wu, Ge
    Yang, Xiaohui
    Shi, Songyang
    Li, Jianning
    JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY, 2020, 57 (06) : 617 - 623