A novel and uniform framework for both face identification and verification is presented in this paper. The framework is based on a combination of Gabor wavelets and General Discriminant Analysis, and can be considered appearance based in that features are extracted from the whole face image. The feature vectors are then subjected to subspace projection. The design of Gabor filters for facial feature extraction is also discussed, which is seldom reported in the literature. The method has been tested extensively for both identification and verification applications. The FERET and BANCA face databases were used to generate the results. Experiments show that Gabor wavelets can significantly improve system performance whilst General Discriminant Analysis outperforms other subspace projection methods such as Principal Component Analysis, Linear Discriminant Analysis, and Kernel Principal Component Analysis. Our method has achieved 97.5% recognition rate on the FERET database, and 5.96% verification error rate on the BANCA database. This is a significantly better performance than that attainable with other popular approaches reported in the literature. In particular, our verification system performed better than most of the systems in the 2004 International Face Verification Competition, using the BANCA face database and specially designed test protocols.

Abstract-A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008.

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Despite research over a long period, biometric approaches t o authenticating personal identity have not met with the degree of success in practical applications originally predicted. This paper discusses approaches t o biometric testing, focusing particularly on automatic signature verification, and addresses some of the important issues which might help t o promote the introduction of practical systems in the future. Examples associated with the adoption of an explicitly flexible approach t o signature verification are used t o illustrate the discussion, and it is argued that there is still considerable potential for practical exploitation of this type of technology.

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