Research on Surface Defect Detection of Aluminum based on Image Processing

DOI
  • Liu Xuemin
    China petroleum engineering & construction corporation
  • Bian Ce
    Tianjin Tianke Intelligent and Manufacture Technology CO., LTD.
  • Yin Di
    Tianjin University of Science and Technology Advanced Structural Integrity International Joint Research Centre, Tianjin University of Science and Technology
  • Zhu Yuxuan
    Tianjin University of Science and Technology Advanced Structural Integrity International Joint Research Centre, Tianjin University of Science and Technology
  • Yuan Yasheng
    Tianjin University of Science and Technology Advanced Structural Integrity International Joint Research Centre, Tianjin University of Science and Technology
  • Wang Hao
    Tianjin University of Science and Technology

Description

Aluminum material is relatively smooth. Aluminum surface engender scratches and bruises easily when collide with other metal. Surface defect detection of aluminum products is particularly important. It is very convenient to use machine vision method for defect detection. Defect contour extraction is an important part of machine vision for defect detection. The surface of aluminum metal is very reflective and shallow scratches are easily mistaken for defects. There are many kinds of filtering, such as the mean filtering, gauss filtering, median filtering and directed filtering. With the help of filtering, dynamic threshold can achieve a good effect. The severe scratch defect and the slight scratch can be clearly separated from the surface of the aluminum product.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390002184876608768
  • DOI
    10.5954/icarob.2020.os15-8
  • ISSN
    21887829
  • Text Lang
    en
  • Data Source
    • JaLC
    • Crossref
  • Abstract License Flag
    Disallowed

Report a problem

Back to top