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 language | English |
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Pages (from-to) | 215-233 |
Journal | Pattern Recognition |
Volume | 34 |
DOIs | |
Publication status | Published - 2001 |