Multimodal biometric systems, which combine information from multiple biometric sources, have shown to improve the identity recognition performance by overcoming the weaknesses and some inherent limitations of unimodal systems. A new framework for score level fusion based on symmetric sums (S-sums) has been presented. These S-sums are generated via triangular norms. The proposed framework has been tested on two publicly available benchmark databases. In particular, the authors used two partitions of NIST-BSSR1, i.e. NIST-multimodal database and NIST-fingerprint database. The experimental results show that the proposed method outperforms the existing approaches for the NIST-multimodal database and NISTfingerprint database.

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This paper presents a compact single-layer UWB antenna based on a coplanar waveguide structure. The antenna operates within bandwidth from 3 to 10.6 GHz (111.76%). The antenna incorporates two notch-filters, designed to mitigate possible interference with WiMAX and WLAN. This filtering function can be switched on or off, independently for each band, by using pin diodes. This feature allows fast adaptation, supporting spectrum sharing solutions with a compact and planar antenna. The simulated and measured results of the proposed antenna are in good agreement, with the maximum antenna gains dropping after activation of the filtering from 2.5 to −10 dBi in WiMAX 3.5 GHz band and from 3 to −8 dBi in WLAN 5 GHz band. K E Y W O R D S CPW-feed, notch band, PIN diode, reconfiguration, UWB monopole antenna

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Biometrics is a scientific technology to recognize a person using their physical, behavior or chemical attributes. Biometrics is nowadays widely being used in several daily applications ranging from smart device user authentication to border crossing. A system that uses a single source of biometric information (e.g., single fingerprint) to recognize people is known as unimodal or unibiometrics system. Whereas, the system that consolidates data from multiple biometric sources of information (e.g., face and fingerprint) is called multimodal or multibiometrics system. Multibiometrics systems can alleviate the error rates and some inherent weaknesses of unibiometrics systems. Therefore, we present, in this study, a novel score level fusion-based scheme for multibiometric user recognition system. The proposed framework is hinged on Asymmetric Aggregation Operators (Asym-AOs). In particular, Asym-AOs are estimated via the generator functions of triangular norms (t-norms). The extensive set of experiments using seven publicly available benchmark databases, namely, National Institute of Standards and Technology (NIST)-Face, NIST-Multimodal, IIT Delhi Palmprint V1, IIT Delhi Ear, Hong Kong PolyU Contactless Hand Dorsal Images, Mobile Biometry (MOBIO) face, and Visible light mobile Ocular Biometric (VISOB) iPhone Day Light Ocular Mobile databases have been reported to show efficacy of the proposed scheme. The experimental results demonstrate that Asym-AOs based score fusion schemes not only are able to increase authentication rates compared to existing score level fusion methods (e.g., min, max, t-norms, symmetric-sum) but also is computationally fast.