Fingerprint and Speaker Verification Decisions Fusion

Authors:
Kar-Ann Toh
Affiliations:
-
Venue:
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Year:
2003

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Abstract

By exploiting the specialist capabilities of each classifier, a combined classi.er may yield results which would not be possible in 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 non-trivial 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 classi.ers 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 network is used to combine the fingerprint and speaker veri.cation decisions with much improved receiver operating characteristics performance as compared to an optimal weighing method.