A Frequency-based Approach for Features Fusion in Fingerprint and Iris Multimodal Biometric Identification Systems

The basic aim of a biometric identification system isto discriminate automatically between subjects in a reliable anddependable way, according to a specific-target application. Multimodalbiometric identification systems aim to fuse two or morephysical or behavioral traits to provide optimal False AcceptanceRate (FAR) and False Rejection Rate (FRR), thus improving systemaccuracy and dependability. In this paper, an innovative multimodalbiometric identification system based on iris and fingerprinttraits is proposed. The paper is a state-of-the-art advancementof multibiometrics, offering an innovative perspective on featuresfusion. In greater detail, a frequency-based approach results ina homogeneous biometric vector, integrating iris and fingerprintdata. Successively, a hamming-distance-based matching algorithmdeals with the unified homogenous biometric vector. The proposedmultimodal system achieves interesting results with several commonlyused databases. For example, we have obtained an interestingworking point with FAR = 0% and FRR = 5.71% usingthe entire fingerprint verification competition (FVC) 2002 DB2Bdatabase and a randomly extracted same-size subset of the BATHdatabase. At the same time, considering the BATH database andthe FVC2002 DB2A database, we have obtained a further interestingworking point with FAR = 0% and FRR = 7.28% ÷ 9.7%.