• DocumentCode
    548918
  • Title

    Recognition of bolt and nut using artificial neural network

  • Author

    Johan, Teuku Muhammad ; Prabuwono, Anton Satria

  • Author_Institution
    Center for Artificial Intell. Technol. (CAIT), Univ. Kebangsaan Malaysia, Bangi, Malaysia
  • Volume
    1
  • fYear
    2011
  • fDate
    28-29 June 2011
  • Firstpage
    165
  • Lastpage
    170
  • Abstract
    This paper focuses on the recognition system of bolt and nut in real time for application in various industries, particularly the automotive industry. The objective of this study is to develop the image processing algorithm to get the normalized cropping images which would be suitable inputs for the learning process using Backpropagation Neural Network. Testing is done using a real-time visual recognition system. The Matlab software version 7.6 is used to integrate all algorithms, whereas the stepper motor differentiates the final result of bolt and nut in separate places. The result shows that the system can detect moving object accurately on the belt conveyor at a speed of 9 cm/sec. with an accuracy 92%.
  • Keywords
    automobile industry; automotive components; backpropagation; conveyors; fasteners; image motion analysis; neural nets; object detection; object recognition; production engineering computing; Matlab software; artificial neural network; automotive industry; backpropagation neural network; belt conveyor; bolt recognition; image processing algorithm; learning process; moving object detection; normalized cropping image; nut recognition; real-time visual recognition system; stepper motor; Artificial neural networks; Fasteners; Humans; Image processing; MATLAB; Training; Pattern recognition; artificial neural network; bolt and nut;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Analysis and Intelligent Robotics (ICPAIR), 2011 International Conference on
  • Conference_Location
    Putrajaya
  • Print_ISBN
    978-1-61284-407-7
  • Type

    conf

  • DOI
    10.1109/ICPAIR.2011.5976889
  • Filename
    5976889