A Novel Hybrid FLANN-PSO Technique for Real Time Fingerprint Classification (Medico Legal Update, 2019)
In this paper we are presenting a Particle swarm optimized functional link neural network for classifying acollection of real time fingerprints in the field of biometric recognition. From the collected fingerprints thefeature vectors are extracted as a collection of different angle oriented features using the Gabor filter bank.The classes of the fingerprints are assigned as per the Henry System. For classification a novel FLANN-PSOalgorithm is used and tested for accuracy through different parameters and different angular features of thefingerprints. In this work we have obtained an accuracy of 98% for real time collected fingerprint images. Ithas been compared with other classifiers and the results obtained of this work in terms of accuracy and MSEvalue has shown appreciable improvement over the other algorithms.