• DocumentCode
    178380
  • Title

    A Two-Dimensional Barcode with Robust Decoding against Distortion and Occlusion for Automatic Recognition of Garbage Bags

  • Author

    Ono, Shintaro ; Kawakami, Y. ; Kawasaki, Hiroshi ; Fujita, S.

  • Author_Institution
    Dept. of Inf. Sci. & Biomed. Eng., Kagoshima Univ., Kagoshima, Japan
  • fYear
    2014
  • fDate
    24-28 Aug. 2014
  • Firstpage
    2879
  • Lastpage
    2884
  • Abstract
    This paper proposes a 2D code and its decoding method robust against non-uniform, complicated distortions, assuming an application to automatic recognition of a plastic garbage bag. Printing a 2D code on a garbage bag is a promising approach for automatic bag recognition from the perspective of information content and cost. However, a 2D code printed on the bag causes non-uniform distortions because the bag is not rigid and does not hold a fixed shape. The proposed 2D code is based on Quick Response (QR) code and has auxiliary lines which allow recognition of distortion and occlusion areas, and the proposed decoding method localizes the lines by reliability calculation and iterated DP matching. Experimental results show that the proposed method in conjunction with the error correction function of QR code could decode the 2D code with non-uniform, non-smooth distortions and occluded areas.
  • Keywords
    bags; bar codes; distortion; error correction; image matching; iterative methods; object recognition; 2D code printing; QR code; automatic garbage bag recognition; automatic plastic garbage bag recognition; distortion area recognition; error correction function; information content; iterated DP matching; nonsmooth distortions; nonuniform distortions; occlusion area recognition; quick response code; robust decoding method; two-dimensional barcode; Decoding; Detectors; Estimation; Feature extraction; Image color analysis; Iterative decoding; Reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2014 22nd International Conference on
  • Conference_Location
    Stockholm
  • ISSN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2014.496
  • Filename
    6977209