• DocumentCode
    163195
  • Title

    Saliency-weighted holistic scene text recognition for unseen place categorization

  • Author

    Thammasorn, Phawis ; Patanukhom, Karn ; Pimup, Rapeeporn

  • Author_Institution
    Dept. of Comput. Eng., Chiang Mai Univ., Chiang Mai, Thailand
  • fYear
    2014
  • fDate
    14-16 May 2014
  • Firstpage
    12
  • Lastpage
    17
  • Abstract
    An improvement in framework for unseen place categorization using scene text is proposed. Category score calculation using visual saliency weighting method is proposed to cope with problem of different importance of word locations on scene images. Additionally, a HOG feature extraction using sliding window is proposed to obtain better holistic word recognition on scene images. As the result, the proposed method outperforms PHOG baseline in unseen place categorization with greater than 10 % improvement in the accuracy.
  • Keywords
    character recognition; feature extraction; HOG feature extraction; category score calculation; holistic word recognition; saliency-weighted holistic scene text recognition; sliding window; unseen place categorization; visual saliency weighting method; word locations; HOG feature; Holistic Scene Text Recognition; Sliding window; Unseen Place Categorization; Visual Saliency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering (JCSSE), 2014 11th International Joint Conference on
  • Conference_Location
    Chon Buri
  • Print_ISBN
    978-1-4799-5821-4
  • Type

    conf

  • DOI
    10.1109/JCSSE.2014.6841834
  • Filename
    6841834