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Paper Abstract and Keywords
Presentation 2018-09-20 10:10
Character Image Clustering for Analyzing Machine-Unreadable Historical Document Images
Sora Ito, Kengo Terasawa (FUN) PRMU2018-46 IBISML2018-23
Abstract (in Japanese) (See Japanese page) 
(in English) For utilization of digital archives which store and publish a lot of historical document images, we think that being shown their indexes or tagged keywords is useful. So, in our laboratory, we are developing a system which extracts keywords from machine-unreadable historical document images without character recognition. In this keyword extraction system, first, we discretize feature vectors by clustering character images expressed by the feature vector. Next, we express sentences with sequences of discretized feature vectors and analyze them. With such a system, we can realize keyword extraction without character recognition. While clustering, if ``separation of clusters'' where one character class is separated into some clusters occurs, the accuracy of keyword extraction decreases. Another problem, In the case of too many character images separated from historical document images, it is difficult to cluster them at once because of computing costs. To solve these problems, in this study, we suggest a clustering method which restrains the separation of clusters and can be adapted in case of too many character images.
Keyword (in Japanese) (See Japanese page) 
(in English) Historical document / Clustering / Document analysis / / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 219, PRMU2018-46, pp. 67-72, Sept. 2018.
Paper # PRMU2018-46 
Date of Issue 2018-09-13 (PRMU, IBISML) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
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)
Download PDF PRMU2018-46 IBISML2018-23

Conference Information
Committee PRMU IBISML IPSJ-CVIM  
Conference Date 2018-09-20 - 2018-09-21 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To PRMU 
Conference Code 2018-09-PRMU-IBISML-CVIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Character Image Clustering for Analyzing Machine-Unreadable Historical Document Images 
Sub Title (in English)  
Keyword(1) Historical document  
Keyword(2) Clustering  
Keyword(3) Document analysis  
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1st Author's Name Sora Ito  
1st Author's Affiliation Future University Hakodate (FUN)
2nd Author's Name Kengo Terasawa  
2nd Author's Affiliation Future University Hakodate (FUN)
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Speaker Author-1 
Date Time 2018-09-20 10:10:00 
Presentation Time 10 minutes 
Registration for PRMU 
Paper # PRMU2018-46, IBISML2018-23 
Volume (vol) vol.118 
Number (no) no.219(PRMU), no.220(IBISML) 
Page pp.67-72 
#Pages 6 
Date of Issue 2018-09-13 (PRMU, IBISML) 

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