• DocumentCode
    149967
  • Title

    Entropy based Script Identification of a multilingual Document Image

  • Author

    Bashir, Rumaan ; Quadri, S.M.K.

  • Author_Institution
    Dept. of Comput. Sci., Islamic Univ. of Sci. & Technol., Awantipora, India
  • fYear
    2014
  • fDate
    5-7 March 2014
  • Firstpage
    19
  • Lastpage
    23
  • Abstract
    Automatic Document Image Analysis has been a prime field of research in the past few decades. Script Identification is an essential part of automatic document image analysis. Script is essentially the text of a written document and languages are written using them. A huge set of techniques have been proposed and many scripts, foreign & domestic, have been identified. But so far, trivial work has been reported for the identification of Kashmiri script. In this paper we are proposing & experimentally testing identification of Kashmiri script collectively with three other related scripts viz. Roman, Devanagri & Urdu using entropy. First, a set of training images are experimented to prepare the knowledge base and later the actual samples have been evaluated. The proposed system offers an accuracy rate of 98.50%.
  • Keywords
    document image processing; entropy; Devanagri script; Kashmiri script identification; Roman script; Urdu script; automatic document image analysis; domestic scripts; entropy based script identification; foreign scripts; languages; multilingual document image; written document; Accuracy; Classification algorithms; Entropy; Feature extraction; Image analysis; Text analysis; Automatic Document Image Analysis; Column Entropy; Devangari; Energy; Entropy; Kashmiri; Multilingual; Quadra-lingual; Roman; Script; Script Identification; Urdu;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing for Sustainable Global Development (INDIACom), 2014 International Conference on
  • Conference_Location
    New Delhi
  • Print_ISBN
    978-93-80544-10-6
  • Type

    conf

  • DOI
    10.1109/IndiaCom.2014.6828005
  • Filename
    6828005