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Idriss Tazight
Sultan Moulay Slimane University
Computer Science & IT Engineering

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Fingerprint Classification Using Fuzzy-neural Network and Other Methods Idriss Tazight; Mohamed Fakir
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 3, No 3: September 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (587.66 KB) | DOI: 10.11591/ijai.v3.i3.pp129-135

Abstract

The fingerprints are unique to each individual; they can be used as a means to distinguish one individual from another.Therefore they are used to identify a person. Fingerprint Classification is done to associate a given fingerprint to one of the existing classes, such as left loop, right loop, arch, tented arch and whorl. Classifying fingerprint images is a very complex pattern recognition problem, due to properties of intra-class diversitiesand inter-class similarities. Its objective is to reduce the responsetime and reducing the search space in an automatic identificationsystem fingerprint (AIS), in classifying fingerprints. In these papers we present a system of fingerprint classificationbased on singular characteristics for extracting feature vectorsand neural networks and fuzzy neural networks, SVM and Knearest neighbour for classifying.
Co-Authors Mohamed Fakir