出版社：Faculty of Humanities, Kaunas University of Technology
其他摘要：In this paper biometric feature systems and multimodal databases for biometric recognition systems are analyzed on the basis of scientific publications in IEEE Xplore digital library. It is shown that wavelet transform coefficients are the most universal feature used in biometric person recognition systems – it is among five frequently used features used in all five popular traits. Moreover, face is the most frequently used trait in multimodal person recognition systems – it is used along with 48 % of iris, 44 % of fingerprint, 33 % of voice and 24 % of signature multimodal systems. Analysis of 15 multimodal databases reveals the fact, that older multimodal databases, e. g., XM2VTS, are still widely used for comparison. However databases such as Biosecure are more versatile and should become more popular soon if a free access will be provided.
