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Publication Citation: Multimodal Biometrics: Issues in Design and Testing

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Author(s): Robert D. Snelick; Michael D. Indovina; James H. Yen; Alan Mink;
Title: Multimodal Biometrics: Issues in Design and Testing
Published: November 01, 2003
Abstract: The results of experimental studies on multimodal biometric systems for small-scale populations have shown better performance compared to single-mode biometric systems. We examine if such techniques scale to larger populations, introduce a methodology to test the performance of such systems, and assess the feasibility of using commercial off-the-shelf (COTS) products to construct deployable multimodal biometric systems. A key aspect of our approach is to leverage confidence level scores from preexisting single-mode data. An example of a multimodal biometrics system analysis is presented that explores various normalization and fusion techniques for face and fingerprint classifiers. This multimodal analysis uses a population of about 1000 subjects, which is a population size ten-times larger than used in any previously reported study. Experimental results combining face and fingerprint biometric classifiers reveal significant performance improvement over single-mode systems.
Conference: International Conference on Multimodal Interfaces
Proceedings: International Conference on Multimodal Interfaces | 5th | | ACM
Location: B.C., -1
Dates: November 5-7, 2003
Keywords: biometric classifiers;biometrics;face and fingerprint biometrics;multimodal biometric systems
Research Areas: Biometrics
PDF version: PDF Document Click here to retrieve PDF version of paper (724KB)