• DocumentCode
    1719860
  • Title

    Characterization of ancient document images composed by Arabic and Latin scripts

  • Author

    Zaghden, Nizar ; Mullot, Remy ; Alimi, Adel M.

  • Author_Institution
    REGIM: Res. Group on Intell. Machines, Univ. of Sfax, Sfax, Tunisia
  • fYear
    2011
  • Firstpage
    124
  • Lastpage
    127
  • Abstract
    In this paper we characterize Arabic and Latin ancient document images. The main criticism of existing works is that most of them are interested in the characterization of Latin historical documents, and they are up to now no many methods that can perform the discrimination between these different language old document images. Regions of images having the same size (256*256 pixels) were extracted from our heterogeneous base. Fractal dimension method is used to discriminate between ancient Arabic and Latin scripts. We achieve 95.87% accuracy on the discrimination between Arabic and Latin ancient document collections. The main advantage of our approach is that it can be easily adapted for the identification of other ancient document collections and we can have better recognition rates by adding relative features of each document base. The encouraging and promising results lead us to study the retrieval of ancient images based on the same technique in order to retrieve similar collections to the image request.
  • Keywords
    document image processing; fractals; image retrieval; Arabic scripts; Latin historical documents characterization; Latin scripts; ancient document image characterization; ancient image retrieval; fractal dimension method; image regions; Character recognition; Fractals; Image matching; Libraries; Noise; Pixel; Robustness; Ancient document discrimination; Arabic and Latin scripts; fractal dimension; image matching; image retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Information Technology (IIT), 2011 International Conference on
  • Conference_Location
    Abu Dhabi
  • Print_ISBN
    978-1-4577-0311-9
  • Type

    conf

  • DOI
    10.1109/INNOVATIONS.2011.5893801
  • Filename
    5893801