Powalka, RK, Sherkat, N and Whitrow, RJ, 1997. Word shape analysis for a hybrid recognition system. Pattern Recognition, 30 (3), pp. 421-445. ISSN 0031-3203
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Abstract
This paper describes two wholistic recognizers developed for use in a hybrid recognition system. The recognizers use information about the word shape. This information is strongly related to word zoning. One of the recognizers is explicitly limited by the accuracy of the zoning information extraction. The other recognizer is designed so as to avoid this limitation. The recognizers use very simple sets of features and fuzzy set based pattern matching techniques. This not only aims to increase their robustness, but also causes problems with disambiguation of the results. A verification mechanism, using letter alternatives as compound features, is introduced. Letter alternatives are obtained from a segmentation based recognizer coexisting in the hybrid system. Despite some remaining disambiguation problems, wholistic recognizers are found capable of outperforming the segmentation based recognizer. When working together in a hybrid system, the results are significantly higher than that of the individual recognizers. Recognition results are reported and compared.
Item Type: | Journal article |
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Publication Title: | Pattern Recognition |
Creators: | Powalka, R.K., Sherkat, N. and Whitrow, R.J. |
Publisher: | Elsevier (not including Cell Press) |
Date: | 1997 |
Volume: | 30 |
Number: | 3 |
ISSN: | 0031-3203 |
Divisions: | Schools > School of Science and Technology |
Record created by: | EPrints Services |
Date Added: | 09 Oct 2015 10:36 |
Last Modified: | 19 Oct 2015 14:34 |
URI: | https://irep.ntu.ac.uk/id/eprint/15350 |
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