• DocumentCode
    1895167
  • Title

    Research on Intelligent Sorting System Based on Machine Vision

  • Author

    Zhi-Ying, Yao ; Yue, Wu ; Wang Cheng-lin

  • Author_Institution
    Key Lab. of Logistics Syst. & Technol., Beijing Inst. of Mater., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    460
  • Lastpage
    463
  • Abstract
    Material sorting system is an important tache in the production logistics and material distribution center, the ability and the speed of sorting system concern the running efficiency of the production logistics and material distribution directly. For the drawbacks of the existing sorting system which only depends on the bar code information, the new intelligent sorting system based on machine vision is purposed and designed in the paper. After getting the original data of material arrived from image collection equipment, the eigenvector used to recognise the material is arrived with all kinds of measurement algorithm. The consistency analysis of the material is realized with intelligent recognition algorithm, which provides the decision-making to the intelligent sorting system.
  • Keywords
    bar codes; computer vision; decision making; eigenvalues and eigenfunctions; image recognition; logistics; materials handling; bar code information; decision making; eigenvector; image collection equipment; intelligent recognition algorithm; intelligent sorting system; machine vision; material distribution center; material sorting system; production logistics; Artificial intelligence; Cameras; Computer vision; Intelligent systems; Logistics; Machine intelligence; Machine vision; Production; Radiofrequency identification; Sorting; Image Processing; Intelligent Sorting System; Machine Vision; Pattern Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
  • Conference_Location
    Changsha, Hunan
  • Print_ISBN
    978-0-7695-3804-4
  • Type

    conf

  • DOI
    10.1109/ICICTA.2009.118
  • Filename
    5287612