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Paper Abstract and Keywords
Presentation 2016-06-16 17:00
Image retrieval in JPEG 2000 codestream domain by a deep learning approach
Yusuke Sugawara (Tokyo Metropolitan Univ), Osamu Watanabe (Takushoku Univ), Sayaka Shiota, Hitoshi Kiya (Tokyo Metropolitan Univ) CAS2016-15 VLD2016-21 SIP2016-49 MSS2016-15
Abstract (in Japanese) (See Japanese page) 
(in English) A codestream-level image retrieval scheme for JPEG 2000 images by
using a deep learning approach is proposed in this
article. The aim is to retrieve similar images to a query image
compressed with the JPEG 2000 standard, from a database in which JPEG
2000 images are labeled according to the similarity among images. The
proposed retrieval scheme can be performed without decoding images because the features used in the
image retrieval can be directly extracted
from JPEG 2000 codestream. In previous research, a codestram-level
retrieval scheme has been studied for JPEG 2000 images. However, it
does not have enough retrieval accuracy, when there are no query
images in the database. The proposed method can improve this problem.
A number of simulations are carried out to confirm the effectiveness
of the proposed scheme.
Keyword (in Japanese) (See Japanese page) 
(in English) JPEG 2000 / Deep Learning / Image Retrieval / / / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 95, SIP2016-49, pp. 79-84, June 2016.
Paper # SIP2016-49 
Date of Issue 2016-06-09 (CAS, VLD, SIP, MSS) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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 CAS2016-15 VLD2016-21 SIP2016-49 MSS2016-15

Conference Information
Committee VLD CAS MSS SIP  
Conference Date 2016-06-16 - 2016-06-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Hirosaki Shiritsu Kanko-kan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) System, signal processing and related topics 
Paper Information
Registration To SIP 
Conference Code 2016-06-VLD-CAS-MSS-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Image retrieval in JPEG 2000 codestream domain by a deep learning approach 
Sub Title (in English)  
Keyword(1) JPEG 2000  
Keyword(2) Deep Learning  
Keyword(3) Image Retrieval  
1st Author's Name Yusuke Sugawara  
1st Author's Affiliation Tokyo Metropolitan University (Tokyo Metropolitan Univ)
2nd Author's Name Osamu Watanabe  
2nd Author's Affiliation Takushoku University (Takushoku Univ)
3rd Author's Name Sayaka Shiota  
3rd Author's Affiliation Tokyo Metropolitan University (Tokyo Metropolitan Univ)
4th Author's Name Hitoshi Kiya  
4th Author's Affiliation Tokyo Metropolitan University (Tokyo Metropolitan Univ)
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Speaker Author-1 
Date Time 2016-06-16 17:00:00 
Presentation Time 20 minutes 
Registration for SIP 
Paper # CAS2016-15, VLD2016-21, SIP2016-49, MSS2016-15 
Volume (vol) vol.116 
Number (no) no.93(CAS), no.94(VLD), no.95(SIP), no.96(MSS) 
Page pp.79-84 
Date of Issue 2016-06-09 (CAS, VLD, SIP, MSS) 

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