The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Un schéma de reconnaissance de segmentation basé sur le lexique sur la reconnaissance de noms de villes manuscrits en bengali est proposé pour l'automatisation postale indienne. Dans le schéma proposé, la binarisation du document d'entrée est d'abord effectuée, puis, pour prendre en compte l'écriture manuscrite inclinée de différentes personnes, une technique de correction d'inclinaison est effectuée. Ensuite, en raison des caractéristiques de l'écriture du Bangla, un concept de réservoir d'eau est appliqué pour pré-segmenter les noms de villes corrigés en biais en possibles. composants primitifs (personnages ou ses parties). Les composants pré-segmentés d'un nom de ville sont ensuite fusionnés en caractères possibles pour obtenir le meilleur nom de ville en utilisant les informations du lexique. Afin de fusionner ces composants primitifs en caractères et de trouver une segmentation optimale des caractères, la programmation dynamique (DP) est appliquée en utilisant la vraisemblance totale des caractères d'un nom de ville comme fonction objective. Pour calculer la vraisemblance d'un caractère, la fonction discriminante quadratique modifiée (MQDF) est utilisée. Les fonctionnalités utilisées dans le MQDF sont principalement basées sur les fonctionnalités directionnelles des points de contour des composants. Nous avons testé notre système sur 84 noms de villes différents en Bangla et une précision de 94.08 % a été obtenue à partir du système proposé.
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Umapada PAL, Kaushik ROY, Fumitaka KIMURA, "A Lexicon-Driven Handwritten City-Name Recognition Scheme for Indian Postal Automation" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 5, pp. 1146-1158, May 2009, doi: 10.1587/transinf.E92.D.1146.
Abstract: A lexicon-driven segmentation-recognition scheme on Bangla handwritten city-name recognition is proposed for Indian postal automation. In the proposed scheme, at first, binarization of the input document is done and then to take care of slanted handwriting of different individuals a slant correction technique is performed. Next, due to the script characteristics of Bangla, a water reservoir concept is applied to pre-segment the slant corrected city-names into possible primitive components (characters or its parts). Pre-segmented components of a city-name are then merged into possible characters to get the best city-name using the lexicon information. In order to merge these primitive components into characters and to find optimum character segmentation, dynamic programming (DP) is applied using total likelihood of the characters of a city-name as an objective function. To compute the likelihood of a character, Modified Quadratic Discriminant Function (MQDF) is used. The features used in the MQDF are mainly based on the directional features of the contour points of the components. We tested our system on 84 different Bangla city-names and 94.08% accuracy was obtained from the proposed system.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.1146/_p
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@ARTICLE{e92-d_5_1146,
author={Umapada PAL, Kaushik ROY, Fumitaka KIMURA, },
journal={IEICE TRANSACTIONS on Information},
title={A Lexicon-Driven Handwritten City-Name Recognition Scheme for Indian Postal Automation},
year={2009},
volume={E92-D},
number={5},
pages={1146-1158},
abstract={A lexicon-driven segmentation-recognition scheme on Bangla handwritten city-name recognition is proposed for Indian postal automation. In the proposed scheme, at first, binarization of the input document is done and then to take care of slanted handwriting of different individuals a slant correction technique is performed. Next, due to the script characteristics of Bangla, a water reservoir concept is applied to pre-segment the slant corrected city-names into possible primitive components (characters or its parts). Pre-segmented components of a city-name are then merged into possible characters to get the best city-name using the lexicon information. In order to merge these primitive components into characters and to find optimum character segmentation, dynamic programming (DP) is applied using total likelihood of the characters of a city-name as an objective function. To compute the likelihood of a character, Modified Quadratic Discriminant Function (MQDF) is used. The features used in the MQDF are mainly based on the directional features of the contour points of the components. We tested our system on 84 different Bangla city-names and 94.08% accuracy was obtained from the proposed system.},
keywords={},
doi={10.1587/transinf.E92.D.1146},
ISSN={1745-1361},
month={May},}
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TY - JOUR
TI - A Lexicon-Driven Handwritten City-Name Recognition Scheme for Indian Postal Automation
T2 - IEICE TRANSACTIONS on Information
SP - 1146
EP - 1158
AU - Umapada PAL
AU - Kaushik ROY
AU - Fumitaka KIMURA
PY - 2009
DO - 10.1587/transinf.E92.D.1146
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2009
AB - A lexicon-driven segmentation-recognition scheme on Bangla handwritten city-name recognition is proposed for Indian postal automation. In the proposed scheme, at first, binarization of the input document is done and then to take care of slanted handwriting of different individuals a slant correction technique is performed. Next, due to the script characteristics of Bangla, a water reservoir concept is applied to pre-segment the slant corrected city-names into possible primitive components (characters or its parts). Pre-segmented components of a city-name are then merged into possible characters to get the best city-name using the lexicon information. In order to merge these primitive components into characters and to find optimum character segmentation, dynamic programming (DP) is applied using total likelihood of the characters of a city-name as an objective function. To compute the likelihood of a character, Modified Quadratic Discriminant Function (MQDF) is used. The features used in the MQDF are mainly based on the directional features of the contour points of the components. We tested our system on 84 different Bangla city-names and 94.08% accuracy was obtained from the proposed system.
ER -