IEICE TRANSACTIONS on Information
Handwritten Postal Code Recognition by Neural Network --A Comparative Study --
Summary :
This paper compares some popular character recognition techniques which have been proposed until today. 17 feature extraction methods and 4 neural network based recognition processes were used in handwritten numerals (postal codes) recognition. It was found that Weighted Direction Index Histogram, Peripheral Direction Contributivity Function and Expansion Cell feature extractions gave good results. As for the neural network recognition process, CombNET-
- Publication
- IEICE TRANSACTIONS on Information Vol.E79-D No.5 pp.443-449
- Publication Date
- 1996/05/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Issue on Character Recognition and Document Understanding)
- Category
- Comparative Study
Authors
Keyword
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Ahmad Fadzil ARIF, Hidekazu TAKAHASHI, Akira IWATA, Toshio TSUTSUMIDA, "Handwritten Postal Code Recognition by Neural Network --A Comparative Study --" in IEICE TRANSACTIONS on Information,
vol. E79-D, no. 5, pp. 443-449, May 1996, doi: .
Abstract: This paper compares some popular character recognition techniques which have been proposed until today. 17 feature extraction methods and 4 neural network based recognition processes were used in handwritten numerals (postal codes) recognition. It was found that Weighted Direction Index Histogram, Peripheral Direction Contributivity Function and Expansion Cell feature extractions gave good results. As for the neural network recognition process, CombNET-
URL: https://global.ieice.org/en_transactions/information/10.1587/e79-d_5_443/_p
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@ARTICLE{e79-d_5_443,
author={Ahmad Fadzil ARIF, Hidekazu TAKAHASHI, Akira IWATA, Toshio TSUTSUMIDA, },
journal={IEICE TRANSACTIONS on Information},
title={Handwritten Postal Code Recognition by Neural Network --A Comparative Study --},
year={1996},
volume={E79-D},
number={5},
pages={443-449},
abstract={This paper compares some popular character recognition techniques which have been proposed until today. 17 feature extraction methods and 4 neural network based recognition processes were used in handwritten numerals (postal codes) recognition. It was found that Weighted Direction Index Histogram, Peripheral Direction Contributivity Function and Expansion Cell feature extractions gave good results. As for the neural network recognition process, CombNET-
keywords={},
doi={},
ISSN={},
month={May},}
Copy
TY - JOUR
TI - Handwritten Postal Code Recognition by Neural Network --A Comparative Study --
T2 - IEICE TRANSACTIONS on Information
SP - 443
EP - 449
AU - Ahmad Fadzil ARIF
AU - Hidekazu TAKAHASHI
AU - Akira IWATA
AU - Toshio TSUTSUMIDA
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E79-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 1996
AB - This paper compares some popular character recognition techniques which have been proposed until today. 17 feature extraction methods and 4 neural network based recognition processes were used in handwritten numerals (postal codes) recognition. It was found that Weighted Direction Index Histogram, Peripheral Direction Contributivity Function and Expansion Cell feature extractions gave good results. As for the neural network recognition process, CombNET-
ER -
English
