• DocumentCode
    690576
  • Title

    Optical Character Recognition (OCR) Performance in Server-Based Mobile Environment

  • Author

    Mantoro, Teddy ; Sobri, Abdul Muis ; Usino, Wendi

  • Author_Institution
    FTI, Univ. of Budi Luhur, Jakarta, Indonesia
  • fYear
    2013
  • fDate
    23-24 Dec. 2013
  • Firstpage
    423
  • Lastpage
    428
  • Abstract
    There are several Optical Character Recognition (OCR) mobile applications on the market running on mobile devices, both android and iOS (iPhone, iPad, iPod) platforms. The limitations of mobile device processor hinder the possible execution of computationally intensive applications that need less time of process. This paper proposes a framework of Optical Character Recognition (OCR) on mobile device using server-based processing. Comparison methods proposed by this paper by conducting a series of tests using standalone and server-based OCR on mobile devices, and compare the results of the accuracy and time required for the entire OCR processing. Server-based mobile OCR obtains 5% higher character recognition accuracy than the standalone OCR and its format recognition accuracy is 99.8%. The framework tries to overcome the limitation of mobile device capability process, so the devices can do the computationally intensive application more quickly.
  • Keywords
    mobile computing; optical character recognition; Android; OCR mobile applications; character recognition accuracy; format recognition accuracy; iOS; iPad; iPhone; iPod; mobile device processor; optical character recognition; server-based OCR; server-based mobile environment; server-based processing; standalone OCR; Accuracy; Cameras; Character recognition; Mobile communication; Mobile handsets; Optical character recognition software; Servers; Optical Character Recognition; accuracy; image processing; mobile device;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Science Applications and Technologies (ACSAT), 2013 International Conference on
  • Conference_Location
    Kuching
  • Type

    conf

  • DOI
    10.1109/ACSAT.2013.89
  • Filename
    6836618