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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Skim pengecaman segmentasi dipacu leksikon pada pengecaman nama bandar tulisan tangan Bangla dicadangkan untuk automasi pos India. Dalam skema yang dicadangkan, pada mulanya, penduaan dokumen input dilakukan dan kemudian untuk menjaga tulisan tangan senget individu yang berbeza teknik pembetulan senget dilakukan. Seterusnya, disebabkan oleh ciri-ciri skrip Bangla, konsep takungan air digunakan untuk membahagikan nama bandar yang dibetulkan condong menjadi mungkin. komponen primitif (watak atau bahagiannya). Komponen prasegmen nama bandar kemudian digabungkan menjadi aksara yang mungkin untuk mendapatkan nama bandar terbaik menggunakan maklumat leksikon. Untuk menggabungkan komponen primitif ini kepada aksara dan untuk mencari pembahagian aksara yang optimum, pengaturcaraan dinamik (DP) digunakan menggunakan jumlah kemungkinan aksara nama bandar sebagai fungsi objektif. Untuk mengira kemungkinan aksara, Fungsi Diskriminasi Kuadratik Ubahsuai (MQDF) digunakan. Ciri-ciri yang digunakan dalam MQDF terutamanya berdasarkan ciri arah titik kontur komponen. Kami menguji sistem kami pada 84 nama bandar Bangla yang berbeza dan 94.08% ketepatan diperoleh daripada sistem yang dicadangkan.
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Salinan
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
Salinan
@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},}
Salinan
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 -