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Paper Abstract and Keywords
Presentation 2022-01-27 13:50
Introduction of auto-associative memory model to zero-watermarking method using hetero-associative memory model
Ryoto Kanegae, Masaki Kawamura (Yamaguchi Univ) EMM2021-86
Abstract (in Japanese) (See Japanese page) 
(in English) We propose a method that introduces an auto-associative memory model to Shimana and Kawamura's method that utilizes a hetero-associative memory model to perform the zero-watermarking method. The zero-watermarking method is a watermarking method that preserves the original image by not embedding the watermark into the image. Since one image is associated with one watermark, it becomes difficult to manage the correspondence when handling a large number of images. Shimana and Kawamura's method is able to manage a large number of correspondences by using a hetero-associative memory model. However, when images are heavily attacked, the features of the images are also degraded. Therefore, the hetero-associative memory model cannot be correctly retrieved them. In this research, we propose a method that introduces an auto-associative memory model. Hence, even if the watermark cannot be correctly recalled by the hetero-associative memory model, the error can be successfully corrected by the auto-associative memory model. The proposed method was evaluated for the cases of JPEG compression and additive white Gaussian noise. As a result, the proposed method was able to reduce the errors of the watermark more effectively than the conventional method.
Keyword (in Japanese) (See Japanese page) 
(in English) Zero-Watermarking / auto-associative memory model / hetero-associative memory model / / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 362, EMM2021-86, pp. 13-18, Jan. 2022.
Paper # EMM2021-86 
Date of Issue 2022-01-20 (EMM) 
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)
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Conference Information
Committee EMM  
Conference Date 2022-01-27 - 2022-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Sense of Presence, Universal Media, Digital Entertainment, etc. 
Paper Information
Registration To EMM 
Conference Code 2022-01-EMM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Introduction of auto-associative memory model to zero-watermarking method using hetero-associative memory model 
Sub Title (in English)  
Keyword(1) Zero-Watermarking  
Keyword(2) auto-associative memory model  
Keyword(3) hetero-associative memory model  
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1st Author's Name Ryoto Kanegae  
1st Author's Affiliation Yamaguchi University (Yamaguchi Univ)
2nd Author's Name Masaki Kawamura  
2nd Author's Affiliation Yamaguchi University (Yamaguchi Univ)
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Speaker Author-1 
Date Time 2022-01-27 13:50:00 
Presentation Time 25 minutes 
Registration for EMM 
Paper # EMM2021-86 
Volume (vol) vol.121 
Number (no) no.362 
Page pp.13-18 
#Pages 6 
Date of Issue 2022-01-20 (EMM) 

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