• DocumentCode
    127417
  • Title

    Real-time classification of industrial products based on the photonic-mixer-device sensor technology

  • Author

    Hussmann, Stephan ; Sandner, Jorn

  • Author_Institution
    Fac. of Eng., West Coast Univ. of Appl. Sci., Heide, Germany
  • fYear
    2014
  • fDate
    18-20 Feb. 2014
  • Firstpage
    267
  • Lastpage
    271
  • Abstract
    During the last years, Time-of-Flight sensors achieved a significant impact onto research fields in machine vision. In comparison to stereo vision system and laser range scanners they combine the advantages of active sensors providing accurate distance measurements and camera-based systems recording a 2D matrix at a high frame rate. Moreover low cost 3D imaging has the potential to open a wide field of additional applications and solutions in markets like consumer electronics, multimedia, digital photography, robotics and medical technologies. This paper focuses on the classification task of typical industrial products in the close-up range. A new approach due to the use of the photonic-mixer-device (PMD) sensor technology is presented which achieves a much simpler real-time classification. Experimental results show that the proposed approach is well suited for machine vision applications.
  • Keywords
    computer vision; distance measurement; image classification; mixers (circuits); optical sensors; real-time systems; distance measurements; industrial products; machine vision applications; photonic-mixer-device sensor technology; real-time classification; Cameras; Logic gates; Modulation; Optical imaging; Optical sensors; Real-time systems; Robot sensing systems; Phase measurement; k-nearest neighbour classification; optical distance measurement component; phase-shift algorithm; photonic mixer devices (PMD); time-of-flight (TOF);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sensors Applications Symposium (SAS), 2014 IEEE
  • Conference_Location
    Queenstown
  • Print_ISBN
    978-1-4799-2180-5
  • Type

    conf

  • DOI
    10.1109/SAS.2014.6798959
  • Filename
    6798959