Paper Abstract and Keywords |
Presentation |
2019-10-03 13:55
Recognition feature prediction from low-resolution iris images using CNN Ryo Watanabe, Keisuke Kameyama (Univ. of Tsukuba) BioX2019-55 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In iris authentication, Daugman's method employing Gabor features is widely supported. However, the method's performance suffers when there are variations in the iris observation conditions. This work aims to improve the authentication performances for cases when only low-resolution images are available upon enrollment and/or verification. In this work, we propose a method to estimate the iris features in the high-resolution (HR) images using low-resolution (LR) images of the same iris. A Convolutional Neural Network (CNN) is used to learn the relation between the local LR feature patch and the HR feature at its center. The estimated HR feature set will be used for authentication. In the experiments, improvements were not observed for the case when HR images were used for enrollment and HR features
estimated from LR images were
used for verification. However, when HR features estimated from LR
images were used for both enrollment and verification, improvements
over the direct use of LR features were observed. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Iris Recognition / image feature / CNN / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 214, BioX2019-55, pp. 5-10, Oct. 2019. |
Paper # |
BioX2019-55 |
Date of Issue |
2019-09-26 (BioX) |
ISSN |
Print edition: ISSN 0913-5685 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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BioX2019-55 |
Conference Information |
Committee |
BioX |
Conference Date |
2019-10-03 - 2019-10-04 |
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(See Japanese page) |
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Paper Information |
Registration To |
BioX |
Conference Code |
2019-10-BioX |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Recognition feature prediction from low-resolution iris images using CNN |
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Iris Recognition |
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image feature |
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CNN |
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1st Author's Name |
Ryo Watanabe |
1st Author's Affiliation |
University of Tsukuba (Univ. of Tsukuba) |
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Keisuke Kameyama |
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University of Tsukuba (Univ. of Tsukuba) |
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Date Time |
2019-10-03 13:55:00 |
Presentation Time |
25 minutes |
Registration for |
BioX |
Paper # |
BioX2019-55 |
Volume (vol) |
vol.119 |
Number (no) |
no.214 |
Page |
pp.5-10 |
#Pages |
6 |
Date of Issue |
2019-09-26 (BioX) |
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