A Multi-Layered Perceptron fingerprint idenfication system

In this work a hybrid technique for classification of fingerprint identification has been developed to decrease the matching time of fingerprint queries. For classification a Multi-Layered Perceptron is described and used. Automatic Fingerprint identification Systems (AFIS) 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 backpropagation algorithm is used to train the system to do correct classification. The classification rate has been estimated to about 88.8 % of unseen fingerprints. A benchmark test shows that the average matching time of a fingerprint is decreased by a factor of 3.7 compared to at total search through the fingerprint database.