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Non intrusive multi-biometrics on a mobile device: a comparison of fusion techniques

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Source: SPIE 2006, conference on Biometric Technology for Human Identification III
Authors: Lorene Allano , Andrew C. Morris, Harin Sellahewa, Sonia Garcia-Salicetti, Jacques Koreman, Sabah Jassim, Bao Ly-Van, Dalei Wu, Bernadette Dorizzi
Keywords: multimodal biometrics, verification, score fusion, Gaussian Mixture Models, smartphone.

Abstract: In this article we test a number of score fusion methods for the purpose of multimodal biometric authentication. These tests were made for the SecurePhone project, whose aim is to develop a prototype mobile communication system enabling biometrically authenticated users to deal legally binding m-contracts during a mobile phone call on a PDA. The three biometrics of voice, face and signature were selected because they are all traditional non-intrusive and easy to use means of authentication which can readily be captured on a PDA. By combining multiple biometrics of relatively low security it may be possible to obtain a combined level of security which is at least as high as that provided by a PIN or handwritten signature, traditionally used for user authentication. As the relative success of different fusion methods depends on the database used and tests made, the database we used was recorded on a suitable PDA (the Qtek2020) and the test protocol was designed to reflect the intended application scenario, which is expected to use short text prompts. Not all of the fusion methods tested are original. They were selected for their suitability for implementation within the constraints imposed by the application. All of the methods tested are based on fusion of the match scores output by each modality. Though computationally simple, the methods tested have shown very promising results. All of the 4 fusion methods tested obtain a significant performance increase.

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