Neural Networks Applied to Fingerprint Recognition

Authors:
Angélica González Arrieta;Griselda Cobos Estrada;Luis Alonso Romero;Ángel Luis Lancho
Affiliations:
Department Informática y Automática, Universidad de Salamanca, Salamanca, Spain 37008;Department Informática y Automática, Universidad de Salamanca, Salamanca, Spain 37008;Department Informática y Automática, Universidad de Salamanca, Salamanca, Spain 37008;Department Informática y Automática, Universidad de Salamanca, Salamanca, Spain 37008
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Year:
2009

Citing 3
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Abstract

In this paper we use a Multi-layer perceptron neural network with learning algorithm retropropagation errors, for application in fingerprint recognition. The objective is to measure the efficiency of the neural network by varying the test data. We observe the behavior of the network in the special case of a partial print. Once the overall structure of the network was designed, tested and properly trained, we proceeded with the testing process, varying the characteristic points and their particular characteristics. Overall, the results demonstrate a stronger recognition when all the characteristic points for the individual prints are available. The recognition rate begins to decrease as the number of characteristic points is reduced to 12, but increases when the number of points is 10, 8 or 5. We obtained a good percentage of hits to remove the features that depended on the center of the footprint and the footprint of the code, in this way to reach the desired goal.