Fingerprint identification – a support vector machine approach
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Original versionKristensen, T. (2010). Fingerprint identification – a support vector machine approach. In J. Filipe, A. Fred, & B. Sharp (Eds.), Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART (pp. 451-458). Setúbal: SciTePress. 10.5220/0002694104510458
In this work a hybrid technique for classification of fingerprint identification has been developed to decrease the matching time. For classification a Support Vector Machine is described and used. Automatic Fingerprint Identification Systems are widely used today, and it is therefore necessary to find a classification system that is less time-consuming. The given fingerprint database is decomposed into four different subclasses and a SVM algorithm is used to train the system to do correct classification. The classification rate has been estimated to about 87.0 % of unseen fingerprints. The average matching time is decreased with a factor of about 3.5 compared to brute force search applied.