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| Presentation | 2019-03-14 11:30 Image Patch Modeling using Secure Computation of Sparse Dictionary Learning Takayuki Nakachi (NTT), Hitoshi Kiya (Tokyo Metro. Univ.)  EMM2018-115 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | With the advent of the big data era, digital content continues to increase. Sparse coding is attracting attention as an information processing model for extracting significant information from a large amount of data. It has been applied to a number of fields including image processing and data analysis, and its effectiveness is recognized. On the other hand, cloud computing is spreading in many fields. However, the cloud computing has some serious issues for end users, such as unauthorized use and leak of data, and privacy compromise, due to unreliability of providers and some accident. In this manuscript, we propose an image modeling method to perform sparse dictionary learning (MOD and K-SVD) on encrypted images. Simulation results show that dictionary learning can be performed on encrypted natural images. It is shown that compared to an image modeling with overcomplete DCT, the proposed method can efficiently extract sparse coefficients. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Dictionary Learning / Sparse Coding / Image Modeling / Random Unitary Transform / Secure Computation / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 494, EMM2018-115, pp. 129-134, March 2019. | |
| Paper # | EMM2018-115 | |
| Date of Issue | 2019-03-06 (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) | |
| Download PDF | EMM2018-115 |
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| Conference Information | |
| Committee | EMM |
| Conference Date | 2019-03-13 - 2019-03-14 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | TBD |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Image and Sound Quality, Metrics for Perception and Recognition, Human Auditory and Visual System, etc. |
| Paper Information | |
| Registration To | EMM |
| Conference Code | 2019-03-EMM |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Image Patch Modeling using Secure Computation of Sparse Dictionary Learning |
| Sub Title (in English) | |
| Keyword(1) | Dictionary Learning |
| Keyword(2) | Sparse Coding |
| Keyword(3) | Image Modeling |
| Keyword(4) | Random Unitary Transform |
| Keyword(5) | Secure Computation |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Takayuki Nakachi |
| 1st Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
| 2nd Author's Name | Hitoshi Kiya |
| 2nd Author's Affiliation | Tokyo Metropolitan University (Tokyo Metro. Univ.) |
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| Speaker | Author-1 |
| Date Time | 2019-03-14 11:30:00 |
| Presentation Time | 25 minutes |
| Registration for | EMM |
| Paper # | EMM2018-115 |
| Volume (vol) | vol.118 |
| Number (no) | no.494 |
| Page | pp.129-134 |
| #Pages | 6 |
| Date of Issue | 2019-03-06 (EMM) |
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