Fingerprint and speaker verification decisions fusion using a functional link network

• Published in: IEEE transactions on systems, man and cybernetics. Part C, Applications and reviews Vol. 35; no. 3; pp. 357 - 370
• Main Authors: Toh, K.-A., Wei-Yun Yau
• Format: Journal Article
• Language: English
• Published: IEEE 01.08.2005
• Subjects: Approximation; Backpropagation; Biometrics; Classifiers; Data fusion; Decisions; Fingerprint recognition; Fingerprints; functional link network and multivariate polynomials; Fusion power generation; Links; Mathematical analysis; Networks; Neural networks; Pattern recognition; Polynomials; Probability; RAKE receivers; Supervised learning
• ISSN: 1094-6977; 1558-2442
• DOI: 10.1109/TSMCC.2005.848184

By exploiting the specialist capabilities of each classifier, a combined classifier may yield results which would not be possible with a single classifier. In this paper, we propose to combine the fingerprint and speaker verification decisions using a functional link network. This is to circumvent the nontrivial trial-and-error and iterative training effort as seen in backpropagation neural networks which cannot guarantee global optimal solutions. In many data fusion applications, as individual classifiers to be combined would have attained a certain level of classification accuracy, the proposed functional link network can be used to combine these classifiers by taking their outputs as the inputs to the network. The proposed network is first applied to a pattern recognition problem to illustrate its approximation capability. The network is then used to combine the fingerprint and speaker verification decisions with much improved receiver operating characteristics performance as compared to several decision fusion methods from the literature.