IEICE TRANSACTIONS on Information
A General Framework and Algorithms for Score Level Indexing and Fusion in Biometric Identification
Summary :
Biometric identification has recently attracted attention because of its convenience: it does not require a user ID nor a smart card. However, both the identification error rate and response time increase as the number of enrollees increases. In this paper, we combine a score level fusion scheme and a metric space indexing scheme to improve the accuracy and response time in biometric identification, using only scores as information sources. We firstly propose a score level indexing and fusion framework which can be constructed from the following three schemes: (I) a pseudo-score based indexing scheme, (II) a multi-biometric search scheme, and (III) a score level fusion scheme which handles missing scores. A multi-biometric search scheme can be newly obtained by applying a pseudo-score based indexing scheme to multi-biometric identification. We secondly propose the NBS (Naive Bayes search) scheme as a multi-biometric search scheme and discuss its optimality with respect to the retrieval error rate. We evaluated our proposal using the datasets of multiple fingerprints and face scores from multiple matchers. The results showed that our proposal significantly improved the accuracy of the unimodal biometrics while reducing the average number of score computations in both the datasets.
- Publication
- IEICE TRANSACTIONS on Information Vol.E97-D No.3 pp.510-523
- Publication Date
- 2014/03/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E97.D.510
- Type of Manuscript
- PAPER
- Category
- Information Network
Authors
Takao MURAKAMI
Hitachi, Ltd.,The University of Tokyo
Kenta TAKAHASHI
Hitachi, Ltd.
Kanta MATSUURA
The University of Tokyo
Keyword
Latest Issue
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Takao MURAKAMI, Kenta TAKAHASHI, Kanta MATSUURA, "A General Framework and Algorithms for Score Level Indexing and Fusion in Biometric Identification" in IEICE TRANSACTIONS on Information,
vol. E97-D, no. 3, pp. 510-523, March 2014, doi: 10.1587/transinf.E97.D.510.
Abstract: Biometric identification has recently attracted attention because of its convenience: it does not require a user ID nor a smart card. However, both the identification error rate and response time increase as the number of enrollees increases. In this paper, we combine a score level fusion scheme and a metric space indexing scheme to improve the accuracy and response time in biometric identification, using only scores as information sources. We firstly propose a score level indexing and fusion framework which can be constructed from the following three schemes: (I) a pseudo-score based indexing scheme, (II) a multi-biometric search scheme, and (III) a score level fusion scheme which handles missing scores. A multi-biometric search scheme can be newly obtained by applying a pseudo-score based indexing scheme to multi-biometric identification. We secondly propose the NBS (Naive Bayes search) scheme as a multi-biometric search scheme and discuss its optimality with respect to the retrieval error rate. We evaluated our proposal using the datasets of multiple fingerprints and face scores from multiple matchers. The results showed that our proposal significantly improved the accuracy of the unimodal biometrics while reducing the average number of score computations in both the datasets.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E97.D.510/_p
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@ARTICLE{e97-d_3_510,
author={Takao MURAKAMI, Kenta TAKAHASHI, Kanta MATSUURA, },
journal={IEICE TRANSACTIONS on Information},
title={A General Framework and Algorithms for Score Level Indexing and Fusion in Biometric Identification},
year={2014},
volume={E97-D},
number={3},
pages={510-523},
abstract={Biometric identification has recently attracted attention because of its convenience: it does not require a user ID nor a smart card. However, both the identification error rate and response time increase as the number of enrollees increases. In this paper, we combine a score level fusion scheme and a metric space indexing scheme to improve the accuracy and response time in biometric identification, using only scores as information sources. We firstly propose a score level indexing and fusion framework which can be constructed from the following three schemes: (I) a pseudo-score based indexing scheme, (II) a multi-biometric search scheme, and (III) a score level fusion scheme which handles missing scores. A multi-biometric search scheme can be newly obtained by applying a pseudo-score based indexing scheme to multi-biometric identification. We secondly propose the NBS (Naive Bayes search) scheme as a multi-biometric search scheme and discuss its optimality with respect to the retrieval error rate. We evaluated our proposal using the datasets of multiple fingerprints and face scores from multiple matchers. The results showed that our proposal significantly improved the accuracy of the unimodal biometrics while reducing the average number of score computations in both the datasets.},
keywords={},
doi={10.1587/transinf.E97.D.510},
ISSN={1745-1361},
month={March},}
Copy
TY - JOUR
TI - A General Framework and Algorithms for Score Level Indexing and Fusion in Biometric Identification
T2 - IEICE TRANSACTIONS on Information
SP - 510
EP - 523
AU - Takao MURAKAMI
AU - Kenta TAKAHASHI
AU - Kanta MATSUURA
PY - 2014
DO - 10.1587/transinf.E97.D.510
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E97-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2014
AB - Biometric identification has recently attracted attention because of its convenience: it does not require a user ID nor a smart card. However, both the identification error rate and response time increase as the number of enrollees increases. In this paper, we combine a score level fusion scheme and a metric space indexing scheme to improve the accuracy and response time in biometric identification, using only scores as information sources. We firstly propose a score level indexing and fusion framework which can be constructed from the following three schemes: (I) a pseudo-score based indexing scheme, (II) a multi-biometric search scheme, and (III) a score level fusion scheme which handles missing scores. A multi-biometric search scheme can be newly obtained by applying a pseudo-score based indexing scheme to multi-biometric identification. We secondly propose the NBS (Naive Bayes search) scheme as a multi-biometric search scheme and discuss its optimality with respect to the retrieval error rate. We evaluated our proposal using the datasets of multiple fingerprints and face scores from multiple matchers. The results showed that our proposal significantly improved the accuracy of the unimodal biometrics while reducing the average number of score computations in both the datasets.
ER -
English
