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Authors: Bo-Ren Zheng 1 ; Dai-Yan Ji 2 and Yung-Hui Li 3

Affiliations: 1 Feng Chia Univerisy, Taiwan ; 2 Advanced Analog Technology and Inc., Taiwan ; 3 National Central University, Taiwan

ISBN: 978-989-758-028-4

Keyword(s): Cross-Sensor Iris Matching, Patch-based Hybrid Dictionary, Sparse Representation.

Related Ontology Subjects/Areas/Topics: Communication and Software Technologies and Architectures ; Computer-Supported Education ; e-Business ; Energy and Economy ; Enterprise Information Systems ; Human-Computer Interaction ; Information Technologies Supporting Learning ; Mobile and Pervasive Computing ; Multimedia Systems ; Security and Privacy ; Sustainable Computing and Communications ; Telecommunications

Abstract: Recently, more and more new iris acquisition devices appear on the market. In practical situation, it is highly possible that the iris images for training and testing are acquired by different iris image sensors. In that case, the recognition rate will decrease a lot and become much worse than the one when both sets of images are acquired by the same image sensors. Such issue is called “cross-sensor iris matching”. In this paper, we propose a novel iris image hallucination method using a patch-based hybrid dictionary learning scheme which is able to hallucinate iris images across different sensors. Thus, given an iris image in test stage which is acquired by a new image sensor, a corresponding iris image will be hallucinated which looks as if it is captured by the old image sensor used in training stage. By matching training images with hallucinated images, the recognition rate can be enhanced. The experimental results show that the proposed method is better than the baseline, which p roves the effectiveness of the proposed image hallucination method. (More)

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Paper citation in several formats:
Zheng, B.; Ji, D. and Li, Y. (2014). Cross-Sensor Iris Matching using Patch-based Hybrid Dictionary Learning.In Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-028-4, pages 169-174. DOI: 10.5220/0004868401690174

@conference{iceis14,
author={Bo{-}Ren Zheng. and Dai{-}Yan Ji. and Yung{-}Hui Li.},
title={Cross-Sensor Iris Matching using Patch-based Hybrid Dictionary Learning},
booktitle={Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2014},
pages={169-174},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004868401690174},
isbn={978-989-758-028-4},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Cross-Sensor Iris Matching using Patch-based Hybrid Dictionary Learning
SN - 978-989-758-028-4
AU - Zheng, B.
AU - Ji, D.
AU - Li, Y.
PY - 2014
SP - 169
EP - 174
DO - 10.5220/0004868401690174

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