• DocumentCode
    595130
  • Title

    A probabilistic framework for logo detection and localization in natural scene images

  • Author

    Roy, Anirban ; Garain, U.

  • Author_Institution
    Comput. Vision & Pattern Recognition Unit, Indian Stat. Inst., Kolkata, India
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    2051
  • Lastpage
    2054
  • Abstract
    This paper presents a probabilistic approach for logo detection and localization in natural scene images. Two probability distributions are computed, one considering the features extracted from the key points located inside a region and the second refers to shape geometry defined by the key points. The barycentric co-ordinates are considered to define the shape statistics. The performance of the proposed approach has been reported on two publicly available datasets: BelgaLogos and Flickr Logos27. It is shown that statistically significant improvement is achieved over a recently proposed method.
  • Keywords
    feature extraction; geometry; natural scenes; object detection; shape recognition; statistical distributions; BelgaLogos; Flickr Logos27; barycentric co-ordinates; feature extraction; natural scene images; probabilistic logo detection framework; probabilistic logo localization framework; probability distribution; publicly available datasets; shape geometry; shape statistics; statistically significant improvement; Accuracy; Databases; Feature extraction; Geometry; Probabilistic logic; Shape; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460563