Unconstrained Arabic Handwritten Word Feature Extraction: A Comparative Study

J. H. AlKhateeb, Jinchang Ren, J. Jiang , S. Ipson

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)

Abstract

This paper presents an overview of feature extraction techniques for unconstrained Arabic handwritten word recognition. Choosing a technique for extraction the features considers the most important factor in achieving high recognition rates in word or character recognition. Different techniques were designed to extract the features from the Arabic words. These techniques are presented and discussed in terms of invariant invariance properties.
Original languageEnglish
Title of host publicationProceedings of the 2009 Sixth International Conference on Information Technology: New Generations
Subtitle of host publicationITNG 2009
PublisherIEEE
Pages1655-1656
Number of pages2
ISBN (Print)978-1-4244-3770-2
DOIs
Publication statusPublished - 2009
EventSixth International Conference on Information Technology - Las Vegas, United States
Duration: 27 Apr 200929 Apr 2009

Conference

ConferenceSixth International Conference on Information Technology
CountryUnited States
CityLas Vegas
Period27/04/0929/04/09

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Keywords

  • application software
  • character recognition
  • discrete cosine transforms
  • feature extraction
  • testing
  • skeleton
  • hidden Markov models
  • optical character recognition software
  • image segmentation

Cite this

AlKhateeb, J. H., Ren, J., Jiang , J., & Ipson, S. (2009). Unconstrained Arabic Handwritten Word Feature Extraction: A Comparative Study. In Proceedings of the 2009 Sixth International Conference on Information Technology: New Generations: ITNG 2009 (pp. 1655-1656). IEEE. https://doi.org/10.1109/ITNG.2009.222