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Arabic (Indian) handwritten digits recognition using gabor-based features

  • Sabri A. Mahmoud

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

Arabic (Indian) handwritten digits recognition is useful in a large variety of banking and business applications and in postal zip code reading, and data entry applications. In this paper we present a technique for the automatic recognition of Arabic (Indian) handwritten digits using Gabor-based features and Support Vector Machines (SVMs). A database consisting of 21120 samples written by 44 writers is used. 70% of the data is used for training and the remaining 30% is used for testing. Several scales and orientations are used to extract the Gaborbased features. The achieved average recognition rates are 99.85% and 97.94% using 3 scales & 5 orientations and using 4 scales & 6 orientations, respectively. The experimental results indicate the effectiveness of the Gabor-based features and SVM for Arabic (Indian) digits recognition.

Original languageEnglish
Title of host publication2008 International Conference on Innovations in Information Technology, IIT 2008
Pages683-687
Number of pages5
DOIs
StatePublished - 2008

Publication series

Name2008 International Conference on Innovations in Information Technology, IIT 2008

Keywords

  • Arabic (Indian) digits
  • Gabor filters
  • Recognition of handwritten arabic numerals
  • Support vector machines

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Software

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