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Paper Abstract and Keywords
Presentation 2013-03-15 14:45
Segmentation-free MRF Recognition Method in Combination with P2DBMN-MQDF for Online Handwritten Cursive Word
Bilan Zhu (Tokyo Univ. of Agriculture and Tech.), Arti Shivram, Srirangaraj Setlur, Venu Govindaraju (Univ. at Buffalo), Masaki Nakagawa (Tokyo Univ. of Agriculture and Tech.) PRMU2012-216
Abstract (in Japanese) (See Japanese page) 
(in English) This paper describes an online handwritten English cursive word recognition method using a segmentation-free Markov random field (MRF) model in combination with an offline recognition method which uses pseudo 2D bi-moment normalization (P2DBMN) and modified quadratic discriminant function (MQDF). It extracts feature points along the pen-tip trace from pen-down to pen-up and uses the feature point coordinates as unary features and the differences in coordinates between the neighboring feature points as binary features. Each character is modeled as a MRF and word MRFs are constructed by concatenating character MRFs according to a trie lexicon of words during recognition. Our method expands the search space using a character-synchronous beam search strategy to search the segmentation and recognition paths. This method restricts the search paths from the trie lexicon of words and preceding paths, as well as the lengths of feature points during path search. Moreover, we combine it with a P2DBMN-MQDF recognizer that is widely used for Chinese and Japanese character recognition.
Keyword (in Japanese) (See Japanese page) 
(in English) Word Recognition / Segmentation-free / Markov Random Field / Modified Quadratic Discriminant Function / Trie Lexicon, Beam Search / / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 495, PRMU2012-216, pp. 213-218, March 2013.
Paper # PRMU2012-216 
Date of Issue 2013-03-07 (PRMU) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee PRMU  
Conference Date 2013-03-14 - 2013-03-15 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2013-03-PRMU 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Segmentation-free MRF Recognition Method in Combination with P2DBMN-MQDF for Online Handwritten Cursive Word 
Sub Title (in English)  
Keyword(1) Word Recognition  
Keyword(2) Segmentation-free  
Keyword(3) Markov Random Field  
Keyword(4) Modified Quadratic Discriminant Function  
Keyword(5) Trie Lexicon, Beam Search  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Bilan Zhu  
1st Author's Affiliation Tokyo University of Agriculture and Technology (Tokyo Univ. of Agriculture and Tech.)
2nd Author's Name Arti Shivram  
2nd Author's Affiliation University at Buffalo (Univ. at Buffalo)
3rd Author's Name Srirangaraj Setlur  
3rd Author's Affiliation University at Buffalo (Univ. at Buffalo)
4th Author's Name Venu Govindaraju  
4th Author's Affiliation University at Buffalo (Univ. at Buffalo)
5th Author's Name Masaki Nakagawa  
5th Author's Affiliation Tokyo University of Agriculture and Technology (Tokyo Univ. of Agriculture and Tech.)
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Speaker Author-1 
Date Time 2013-03-15 14:45:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2012-216 
Volume (vol) vol.112 
Number (no) no.495 
Page pp.213-218 
#Pages 6 
Date of Issue 2013-03-07 (PRMU) 

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