Fingerprint and Face Recognition System using A Feed-Forward Artificial Neural Network Paradigm

Authors : Ene Princewill Chigozie

Volume/Issue : Volume 7 - 2022, Issue 8 - August

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This research presents the development of intelligent techniques for fingerprint and faces recognition systems. This was achieved following data collection, data acquisition, data processing, artificial intelligence, training, and result presentation. The intelligent technique was modeled using the structural method to develop the algorithm for face and fingerprint verification systems. The algorithms were implemented with Simulink. The result showed that the average Means Squre Error(MSE) for face is 4.7E-05Mu, that for the fingerprint is 2.05E-05; the regression value for face is 0.973 and 0.995 for the finger. The algorithm was deployed as a face and fingerprint verification system and the result were tested and validated using a tenfold cross-validation approach. An accuracy of 98.6% was achieved for face recognition and 98.87% was achieved for fingerprint verification results. The performance was compared with other algorithms and it was observed that the new algorithm performs better.

Keywords : Face Recognition, Fingerprint Verification, Training, Artificial Intelligence, Simulink, Artificial Neural Network (ANN).


Paper Submission Last Date
29 - February - 2024

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