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  1. B200 工学部/工学研究科
  2. B200a 雑誌掲載論文
  3. 学術雑誌

A study of symbol segmentation method for handwritten mathematical formula recognition using mathematical structure information

http://hdl.handle.net/2237/6870
http://hdl.handle.net/2237/6870
3a850ef0-7b8f-4ddf-8afa-0fae7febb2e2
名前 / ファイル ライセンス アクション
studyofsymbolsegmentation.pdf studyofsymbolsegmentation.pdf (478.0 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2006-08-28
タイトル
タイトル A study of symbol segmentation method for handwritten mathematical formula recognition using mathematical structure information
言語 en
著者 Toyozumi, Kenichi

× Toyozumi, Kenichi

WEKO 13373

en Toyozumi, Kenichi

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Yamada, Naoya

× Yamada, Naoya

WEKO 13374

en Yamada, Naoya

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Kitasaka, Takayuki

× Kitasaka, Takayuki

WEKO 13375

en Kitasaka, Takayuki

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Mori, Kensaku

× Mori, Kensaku

WEKO 13376

en Mori, Kensaku

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Suenaga, Yasuhito

× Suenaga, Yasuhito

WEKO 13377

en Suenaga, Yasuhito

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Mase, Kenji

× Mase, Kenji

WEKO 13378

en Mase, Kenji

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Takahashi, Tomoichi

× Takahashi, Tomoichi

WEKO 13379

en Takahashi, Tomoichi

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アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利
言語 en
権利情報 Copyright © 2004 IEEE. Reprinted from (relevant publication info). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Nagoya University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org.
抄録
内容記述 Symbol segmentation is very important in handwritten mathematical formula recognition, since it is the very first portion of the recognition, since it is the very first portion of the recognition process. This paper proposes a new symbol segmentation method using mathematical structure information. The base technique of symbol segmentation employed in theexisting methods is dynamic programming which optimizes the overall results of individual symbol recognition. The new method we propose here improves symbol recognition performance by using correction values of symbol recognition. These correction values sre calculated from the relations among handwritten stroke positions and mathematical structure. There is no report which takes account of mathematical structure information for synbol segmentation in the handwritten mathematical formula recognition. Our experiments have proven that the recognition rate of symbol segmentation by existing methods is between 90.2% and 93.3% while our proposed method gives correct recognition rate of 97.1%.
言語 en
内容記述タイプ Abstract
出版者
言語 en
出版者 IEEE
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1109/ICPR.2004.1334327
書誌情報 en : Proceedings of the 17th International Conference on Pattern Recognition

巻 2, p. 630-633, 発行日 2004-08
フォーマット
application/pdf
著者版フラグ
値 publisher
URI
識別子 http://hdl.handle.net/2237/6870
識別子タイプ HDL
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