Automatic fingerprint classification system using fuzzy neural techniques

This paper reviews the fingerprint classification for its performance in the fingerprint identification systems. Fingerprint recognition can be applied to access control systems used in restricted areas, criminal recognition, forensic labs, and as a substitute for PIN numbers on cards or electronics access. The scheme is based 017 fingerprint classification feature extraction and testing a simple and flexible fingerprint classification algorithm,. Our attempt is to allow the accuracy and speed zip of the automatic fingerprint identification algorithms to improve the quality of the existing and the future systems. We used Fuzzy Self Organizing Map (FSOM) to implement the classification, in this purpose a FSOM classifier is trained to analyze. The technique extracts the singular points (Core and Delta points) in fingerprints obtained from directional threshold not minutiae neighborhoods and to decide whether they are valid or not.