• DocumentCode
    3489294
  • Title

    An Anytime Algorithm for Camera-Based Character Recognition

  • Author

    Kobayashi, Takehiko ; Iwamura, Mikio ; Matsuda, Tadamitsu ; Kise, Kenji

  • Author_Institution
    Grad. Sch. of Eng., Osaka Prefecture Univ., Sakai, Japan
  • fYear
    2013
  • fDate
    25-28 Aug. 2013
  • Firstpage
    1140
  • Lastpage
    1144
  • Abstract
    In a scene image, some characters are difficult to recognize and some others are recognized easily. Such difficult characters usually make the processing time long while easy characters are recognized in a short time. In this paper, we propose a system which recognizes each character with a proper cost for the difficulty. Through the process, easy characters are recognized early and difficult ones are recognized late. This is a desired property of an anytime algorithm that the recognition accuracy does not decrease as the time increases. In order to realize it, we propose a method which splits the recognition process into several times and accumulates the recognition results and extracted features. We also discuss what is required to realize the anytime algorithm for the scene character recognition task. Experiments reveal that the proposed method obtains recognition results of easy characters earlier than the conventional method.
  • Keywords
    character recognition; feature extraction; image recognition; anytime algorithm; camera-based character recognition; feature extraction; recognition accuracy; scene character recognition; scene image recogntion; Accuracy; Character recognition; Computational efficiency; Feature extraction; Image recognition; Robustness; Shape; ASIFT; anytime algorithm; local feature; scene character recognition; tracking; video input;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2013.231
  • Filename
    6628792