• DocumentCode
    2521533
  • Title

    Online recognition of multi-stroke handwritten Urdu characters

  • Author

    Khan, Kamran Ullah ; Haider, Ihtesham

  • Author_Institution
    DEE, PIEAS, Islamabad, Pakistan
  • fYear
    2010
  • fDate
    9-11 April 2010
  • Firstpage
    284
  • Lastpage
    290
  • Abstract
    Character recognition has enjoyed a lot of research in the recent past. Good recognition systems are available commercially for alphabetical languages based on Roman characters and for symbolic languages like Chinese. But languages based on Arabic alphabets like Arabic, Urdu etc. do not have such recognition systems. The recognition systems generally have a scanner or camera as the input device for off-line recognition, or a stylus/tablet as input device for online recognition. These systems are used in conjunction with the input peripheral devices like keyboards and mice. With the recent developments in electronic tablets, pen movements can be captured more accurately. This paper presents part of the work for online recognition of handwritten Urdu language characters. Urdu language is based on Arabic alphabets with larger character set as compared to Arabic (37 characters). Urdu, due to its large character set and limited number strokes, is difficult to recognize. Many characters are similar with little differences. Online recognition of multi stroke (two-, three-, and four-stroke) handwritten Urdu characters is presented in this paper, whereas, single-stroke character recognition was presented in a preceding work. After necessary preprocessing, some novel features are extracted. Various types of classification methodologies are then tested in order to find the best combination of features and classifiers for two-, three-, and four-strokes handwritten Urdu characters recognition.
  • Keywords
    cameras; feature extraction; handwritten character recognition; image scanners; keyboards; light pens; mouse controllers (computers); natural languages; Arabic alphabets; Roman characters; alphabetical languages; camera; character recognition; classifiers; electronic tablets; feature extraction; input peripheral devices; multi-stroke handwritten Urdu characters; off-line recognition; online recognition; pen movements; recognition systems; scanner; symbolic languages; Cameras; Character recognition; Feature extraction; Handwriting recognition; Keyboards; Mice; Natural languages; Neural networks; Testing; Writing; Back Propagation Neural Network; Correlation based Classifier; Major Stroke; Minor Stroke; Online Characters Recognition; Probabilistic Neural Network; Template Matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Signal Processing (IASP), 2010 International Conference on
  • Conference_Location
    Zhejiang
  • Print_ISBN
    978-1-4244-5554-6
  • Electronic_ISBN
    978-1-4244-5556-0
  • Type

    conf

  • DOI
    10.1109/IASP.2010.5476113
  • Filename
    5476113