Fingerprints are the biometric features most used for detection. Dormant prints are routinely recovered commencing crime scenes and are comparing with existing databases of notorious fingerprints for identifying criminals. A lot of matching algorithms with different uniqueness have been introduced in recent years. For real time systems these algorithms are usually based on minutiae features. The detection of known systems tries to find which fingerprint in a database matches the fingerprint requires the matching of its minutiae against the input fingerprint. Since the detection intricacy is many minutiae of other fingerprints. Hence, fingerprint matching is a higher than verification, detection systems usually accept key process. This paper introduced study on a novel approach like Minutia Cylinder Code (MCC) algorithm, Graphic Processing Unit (GPU) and Biometric Encryption for security purpose also for feature extraction in which the extracted features are self-determining of shift and rotation of the fingerprint and at the meantime the matching operation is performed much more easily and with higher alacrity and accuracy.

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Minutiae Latent Prints Alacrity Minutia Cylinder Code (mcc)