An Arabic optical character recognition system using recognition-based segmentation

A. Cheung, Mohammed Bennamoun, N.W. Bergmann

    Research output: Contribution to journalArticlepeer-review

    89 Citations (Scopus)

    Abstract

    Optical character recognition (OCR) systems improve human-machine interaction and are widely used in many areas. The recognition of cursive scripts is a difficult task as their segmentation suffers from serious problems. This paper proposes an Arabic OCR system, which uses a recognition-based segmentation technique to overcome the classical segmentation problems. A newly developed Arabic word segmentation algorithm is also introduced to separate horizontally overlapping Arabic words/subwords. There is also a feedback loop to control the combination of character fragments for recognition. The system was implemented and the results show a 90% recognition accuracy with a 20 chars/s recognition rate. (C) 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
    Original languageEnglish
    Pages (from-to)215-233
    JournalPattern Recognition
    Volume34
    DOIs
    Publication statusPublished - 2001

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