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| Presentation | 2021-08-26 16:00 A Study of Low-Resolution Iris Biometrics using Single Image Super-Resolution Tsubasa Bora, Daisuke Uenoyama (UEC), Takahiro Toizumi, Yuka Ogino, Masato Tsukada (NEC), Masatsugu Ichino (UEC)  PRMU2021-14 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | It requires a high-quality iris image in general, which means that subject must look into the camera, which is highly intrusive on subject and expensive high-resolution camera limits the using scene. Image super-resolution (SR) methods were applied to iris recognition. The evaluation was used hand-crafted feature extractors but there are not enough evaluations using CNN-based feature extractors. We experimented in iris recognition with combinations of SR methods and CNN-based feature extractors and evaluated the accuracy for each combination. The results showed that the best combination depended on targets of iris diameter, that is iris resolution. The one cause was considered attention area of feature extractor and noise of SR image. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Biometrics / Iris Recognition / Deep Learning / CNN / Super Resolution / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 155, PRMU2021-14, pp. 42-47, Aug. 2021. | |
| Paper # | PRMU2021-14 | |
| Date of Issue | 2021-08-19 (PRMU) | |
| 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 | PRMU2021-14 |
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| Conference Information | |
| Committee | PRMU |
| Conference Date | 2021-08-26 - 2021-08-26 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | CV/PR techniques for human-robot cooperation |
| Paper Information | |
| Registration To | PRMU |
| Conference Code | 2021-08-PRMU |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study of Low-Resolution Iris Biometrics using Single Image Super-Resolution |
| Sub Title (in English) | |
| Keyword(1) | Biometrics |
| Keyword(2) | Iris Recognition |
| Keyword(3) | Deep Learning |
| Keyword(4) | CNN |
| Keyword(5) | Super Resolution |
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| 1st Author's Name | Tsubasa Bora |
| 1st Author's Affiliation | The University of Electro-Communications (UEC) |
| 2nd Author's Name | Daisuke Uenoyama |
| 2nd Author's Affiliation | The University of Electro-Communications (UEC) |
| 3rd Author's Name | Takahiro Toizumi |
| 3rd Author's Affiliation | NEC Corporation (NEC) |
| 4th Author's Name | Yuka Ogino |
| 4th Author's Affiliation | NEC Corporation (NEC) |
| 5th Author's Name | Masato Tsukada |
| 5th Author's Affiliation | NEC Corporation (NEC) |
| 6th Author's Name | Masatsugu Ichino |
| 6th Author's Affiliation | The University of Electro-Communications (UEC) |
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| Speaker | Author-1 |
| Date Time | 2021-08-26 16:00:00 |
| Presentation Time | 15 minutes |
| Registration for | PRMU |
| Paper # | PRMU2021-14 |
| Volume (vol) | vol.121 |
| Number (no) | no.155 |
| Page | pp.42-47 |
| #Pages | 6 |
| Date of Issue | 2021-08-19 (PRMU) |
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