• DocumentCode
    2623637
  • Title

    Document image binarization by using texture-edge descriptor

  • Author

    Armanfard, N. ; Valizadeh, M. ; Komeili, M. ; Kabir, E.

  • Author_Institution
    Dept. of Electr. Eng., Tarbiat Modarres Univ., Tehran, Iran
  • fYear
    2009
  • fDate
    20-21 Oct. 2009
  • Firstpage
    134
  • Lastpage
    139
  • Abstract
    In this paper we propose a new approach for text region extraction in camera-captured document images. Texture-Edge Descriptor, TED, is utilized for text region extraction. TED is an 8-bit binary number which its bits are structural. This structural bits and special text region characteristics in document images make TED an appropriate descriptor for text region extraction. Applying well-known water flow method to the text regions extracted by TED, results in fast and good quality document image binarization. Experimental results demonstrate the effectiveness of our method for text region extraction and document image binarization.
  • Keywords
    document image processing; feature extraction; document image binarization; text region extraction; texture-edge descriptor; water flow method; Background noise; Character recognition; Image edge detection; Image segmentation; Image texture analysis; Pixel; Text analysis; binarization; document image; texture-edge descriptor; water flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Conference, 2009. CSICC 2009. 14th International CSI
  • Conference_Location
    Tehran
  • Print_ISBN
    978-1-4244-4261-4
  • Electronic_ISBN
    978-1-4244-4262-1
  • Type

    conf

  • DOI
    10.1109/CSICC.2009.5349330
  • Filename
    5349330