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A novel lexicon reduction method for arabic handwriting recognition

  • SUNY Buffalo
  • Wuhan University of Technology
  • Applied Media Analysis, Inc.

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

14 Scopus citations

Abstract

In this paper, we present a method for lexicon size reduction which can be used as an important pre-processing for an off-line Arabic word recognition. The method involves extraction of the dot descriptors and PAWs (Piece of Arabic Word). Then the number and position of dots and the number of the PAWs are used to eliminate unlikely candidates. The extraction of the dot descriptors is based on defined rules followed by a convolutional neural network for verification. The reduction algorithm makes use of the combination of two features with a dynamic matching scheme. On IFN/ENIT database of 26459 Arabic handwritten word images we achieved a reduction rate of 87% with accuracy above 93%.

Original languageEnglish
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
Pages2865-2868
Number of pages4
DOIs
StatePublished - 2010
Event2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
Duration: Aug 23 2010Aug 26 2010

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Conference

Conference2010 20th International Conference on Pattern Recognition, ICPR 2010
Country/TerritoryTurkey
CityIstanbul
Period08/23/1008/26/10

Keywords

  • Arabic offline handwritten
  • Handwritten recognition
  • Lexicon redeuction

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