Indexing biometric databases using pyramid technique

Authors:
Amit Mhatre;Sharat Chikkerur;Venu Govindaraju
Affiliations:
Center for Unified Biometrics and Sensors (CUBS), University at Buffalo, New York;Center for Unified Biometrics and Sensors (CUBS), University at Buffalo, New York;Center for Unified Biometrics and Sensors (CUBS), University at Buffalo, New York
Venue:
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Year:
2005

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Abstract

Biometric identification has emerged as a reliable means of controlling access to both physical and virtual spaces. In spite of the rapid proliferation of large-scale databases, the research has thus far been focused only on accuracy within small databases. However, as the size of the database increases, not only does the response time deteriorate, but so does the accuracy of the system. Thus for larger applications it is essential to prune the database to a smaller fraction which would not only ensure higher speeds, but also aid in achieving higher accuracy. Unlike structured information such as text or numeric data that can be sorted, biometric data does not have a natural sorting order making indexing the biometric database a challenging problem. In this paper we show the efficacy of indexing hand geometry biometric using the Pyramid Technique, to reduce the search space to just 8.86% of the entire database, while maintaining a 0% FRR.