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Paper Abstract and Keywords
Presentation 2019-09-19 15:35
Digital watermarking method against print-cam attack using deep learning for synchronization
Hiroyuki Imagawa, Motoi Iwata, Koichi Kise (Osaka Pref. Univ.) LOIS2019-12 IE2019-25 EMM2019-69
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a novel watermarking method against print-cam attack.
Digital watermarking is used to get information from a printed watermarked image by taking.
In such applications, synchronization between a non-attacked watermarked image and print-cam attacked one needs high accuracy.
To achieve this, we use deep learning which is used for image recognition, image detection, and semantic segmentation.
We trained deep learning model whether watermarked image area or non-watermarked image area as semantic segmentation.
For the detection, estimate a watermarked image area from the result predicted by the deep learning model.
As a result of training, deep learning model with the data set which is consisted of warped watermarked and non-watermarked images got high accuracy of $99%$ mIoU.
Keyword (in Japanese) (See Japanese page) 
(in English) Digital watermarking / Deep learning / Semantic segmentation / Print-cam / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 207, EMM2019-69, pp. 31-36, Sept. 2019.
Paper # EMM2019-69 
Date of Issue 2019-09-12 (LOIS, IE, EMM) 
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 LOIS2019-12 IE2019-25 EMM2019-69

Conference Information
Conference Date 2019-09-19 - 2019-09-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokimeito, Niigata University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To EMM 
Conference Code 2019-09-IE-EMM-LOIS-CMN-ME-AVM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Digital watermarking method against print-cam attack using deep learning for synchronization 
Sub Title (in English)  
Keyword(1) Digital watermarking  
Keyword(2) Deep learning  
Keyword(3) Semantic segmentation  
Keyword(4) Print-cam  
1st Author's Name Hiroyuki Imagawa  
1st Author's Affiliation Osaka Prefecture University (Osaka Pref. Univ.)
2nd Author's Name Motoi Iwata  
2nd Author's Affiliation Osaka Prefecture University (Osaka Pref. Univ.)
3rd Author's Name Koichi Kise  
3rd Author's Affiliation Osaka Prefecture University (Osaka Pref. Univ.)
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Date Time 2019-09-19 15:35:00 
Presentation Time 25 
Registration for EMM 
Paper # LOIS2019-12, IE2019-25, EMM2019-69 
Volume (vol) 119 
Number (no) no.205(LOIS), no.206(IE), no.207(EMM) 
Page pp.31-36 
Date of Issue 2019-09-12 (LOIS, IE, EMM) 

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