Abstract
Recent works about perceptron-based fusion of multiple fingerprint matchers showed the effectiveness of such approach in improving the performance of personal identity verification systems. However, to the best of our knowledge, no previous work investigated such fusion approach when stringent requirements in terms of verification errors are given, and the number of available samples for perceptron training is small. Such investigation can allow to understand for which kind of applications such fusion rule can be useful. Reported experiments, based on two benchmark data sets, show that perceptron-based fusion can be useful for high security fingerprint verification applications, and it is effective in small-sample-size realistic cases.
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Marcialis, G.L., Roli, F. (2004). High Security Fingerprint Verification by Perceptron-Based Fusion of Multiple Matchers. In: Roli, F., Kittler, J., Windeatt, T. (eds) Multiple Classifier Systems. MCS 2004. Lecture Notes in Computer Science, vol 3077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25966-4_36
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DOI: https://doi.org/10.1007/978-3-540-25966-4_36
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