NDLI: Score level fusion of hand based biometrics using t-norms

Content Provider	IEEE Xplore Digital Library
Author	Hanmandlu, M. Grover, J. Madasu, V.K. Vasirkala, S.
Copyright Year	2010
Description	Author affiliation: American Intercontinental University (Vasirkala, S.) \|\| Department of Electrical Engineering, Indian Institute of Technology, Delhi, India (Hanmandlu, M.; Grover, J.) \|\| NICTA, Austrailia (Madasu, V.K.)
Abstract	A multimodal biometric system amalgamates the information from multiple biometric sources to alleviate the limitations in performance of each individual biometric system. In this paper a multimodal biometric system employing hand based biometrics (i.e. palmprint, hand veins, and hand geometry) is developed. A general combination approach is proposed for the score level fusion which combines the matching scores from these hand based modalities using t-norms due to Hamacher, Yager, Weber, Schweizer and Sklar. This study aims at exploring the potential usefulness of t-norms for multimodal biometrics. These norms deal with the real challenge of uncertainty and imperfection pervading the different sources of knowledge (scores from different modalities). We construct the membership functions of fuzzy sets formed from the genuine and imposter scores of each of the modalities considered. The fused genuine score and imposter scores are obtained by integrating the fuzzified genuine scores and imposter scores respectively from each of the modalities. These norms are relatively very simple to apply unlike the other methods (example SVM, decision trees, discriminant analysis) as no training or any learning is required here. The proposed approach renders very good performance as it is quite computationally fast and outperforms the score level fusion using the conventional rules (min, max, sum, median) The experimental evaluation on a database of 100 users confirms the effectiveness of score level fusion. The preliminary results are encouraging in terms of decision accuracy and computing efficiency.
Starting Page	70
Ending Page	76
File Size	1724004
Page Count	7
File Format	PDF
ISBN	9781424460472
e-ISBN	9781424460489
DOI	10.1109/THS.2010.5655093
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Geometry Training Support vector machines score level Veins Multimodal fusion t-norm Face Iris recognition
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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