• DocumentCode
    2777636
  • Title

    An effective segmentation method for single stroke online cursive Arabic words

  • Author

    Potrus, Moayad Yousif ; Ngah, Umi Kalthum ; Sakim, Harsa Amylia Mat

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Univ. Sains Malaysia, Nibong Tebal, Malaysia
  • fYear
    2010
  • fDate
    5-8 Dec. 2010
  • Firstpage
    217
  • Lastpage
    221
  • Abstract
    A new method is used for character segmentation from cursive Arabic words. The method is based on statistical approach which uses Normalization and rectification, coordinate transformation and clustering to extract ligatures. The output is then filtered to extract start, overlapped and end segment errors. After applying the filter the characters are completely isolated and ready for recognition. The system, when testing the segmentation on 5 different Arabic sentences and by 20 different users, scored 98.03%, 94.82, 97.33 and 90% for normal segment, starting segment, last segment and overlapped segment.
  • Keywords
    feature extraction; handwritten character recognition; image segmentation; natural language processing; pattern clustering; character segmentation; clustering; coordinate transformation; ligatures extraction; normalization; rectification; single stroke online cursive Arabic words; Character recognition; Equations; Filtering; Handwriting recognition; Joints; Shape; Writing; Arabic Word Ligatures; Character Segmentation; Single Stroke;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-9054-7
  • Type

    conf

  • DOI
    10.1109/ICCAIE.2010.5735078
  • Filename
    5735078