• DocumentCode
    2316101
  • Title

    Empty bottle inspector based on machine vision

  • Author

    Duan, Feng ; Wang, Yao-Nan ; Liu, Huan-jun ; Tan, Wen

  • Author_Institution
    Coll. of Electr. & Information Eng., Hunan Univ., Changsha, China
  • Volume
    6
  • fYear
    2004
  • fDate
    26-29 Aug. 2004
  • Firstpage
    3845
  • Abstract
    A machine-vision-based empty bottle inspector is presented in this paper. The mechanical structure and electric control system are illustrated in detail. A method based on the histogram of edge points is applied for real-time determination of inspection area. For defect detection of bottle wall and bottle bottom, a derivative algorithm from Canny edge detector is proposed. In bottle finish inspection, two artificial neural networks are used for low-level inspection and high-level judgment respectively. A prototype is developed and experimental results demonstrate the feasibility of the inspector. Inspections performed by the prototype have proved the effectiveness and value of the proposed algorithms in automatic real-time inspection.
  • Keywords
    automatic optical inspection; brewing industry; computer vision; edge detection; neural nets; recycling; Canny edge detector; artificial neural network; bottle finish inspection; defect detection; electric control system; empty bottle inspector; machine vision; mechanical structure; Control systems; Humans; Image edge detection; Inspection; Machine vision; Particle separators; Production; Prototypes; Sensor systems; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1380507
  • Filename
    1380507