Comparative Study on Statistical Data Value Technique for Fake Fingerprint Classification: Array

Fingerprint detection is a biometric technology that widely use as security purpose, either in smartphone, building or house and banking withdrawal transaction. However, fingerprint can be forged by using materials such as latex, silicone or gelatin, to make fake fingerprints. Despite, the ability to fool the fingerprint detection system, fake fingerprint still has some issues because of the presence of noise. In order to detect the fake fingerprint images and forbid any unwanted or criminal act that use the weakness of fingerprint detection system, the statistical data value technique that represent the fake fingerprint images must has a high accuracy data representative. To obtain a high accuracy of data representative, the best techniques must be investigated. Therefore, this paper presents a comparative study on finding the most accurate statistical data value techniques to classify the fake fingerprint images.