An Arabic optical character recognition system using recognition-based segmentation

نویسندگان

  • A. Cheung
  • Mohammed Bennamoun
  • Neil W. Bergmann
چکیده

Optical character recognition (OCR) systems improve human}machine interaction and are widely used in many areas. The recognition of cursive scripts is a di$cult task as their segmentation su!ers 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. ( 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

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عنوان ژورنال:
  • Pattern Recognition

دوره 34  شماره 

صفحات  -

تاریخ انتشار 2001