Arabic text recognition using steady state genetic algorithm

Abdullah M. Al-Mutawa, Chilukuri K. Mohan

Research output: Contribution to journalArticle

Abstract

Text recognition is a challenging task when text contains overlapping and cursive characters. This paper addresses the task of matching input Arabic text with character forms in the database described in terms of features. We introduce new features that approximate character shapes, designed to make the recognition process independent of font size. We apply steady state genetic algorithms to the partial shape-matching task, with extremely encouraging recognition rate. No separate segmentation is required in our approach.

Original languageEnglish (US)
Pages (from-to)311-316
Number of pages6
JournalIntelligent Engineering Systems Through Artificial Neural Networks
Volume1998
StatePublished - Dec 1 1998

Keywords

  • Character Recognition
  • Edge Detection
  • Feature Extraction
  • Genetic Algorithms

ASJC Scopus subject areas

  • Software

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