Hyper spectral face image based biometric recognition

Day to day life is more unsecure as per the hacking is concerned. Our data is not secure because it can be stolen, hacked, destroy, manipulate, password may forget, guess, Card, token, etc. To overcome this problem biometrics is used as a strong authentication system. The person should be present at the time of the instance. Biometric security is challenging task in day to day life because it is difficult to avoid the fraud. In this research paper emerging biometric trait, i.e. Hyper Spectral Face is considered for human authentication system. There are various visible spectrum of electromagnetic spectral bands are considered for face recognition instead of only three RGB bands. Hyper Spectral gives band wise more finite detail information on face. It is very novel and more accurate than ordinary face recognition system. Hong Kong PolyU Hyper Spectral Face Database used for Face recognition. Kernel Principle Component Analysis (KPCA) algorithm gives prominent features of the Hyperspectral Face Dataset. Extracted features are classified by Mahalinobis Cosine (Mahcos) similarity measurement technique. The Recognition rate calculated on the basis of One Rank Level it furnishes 69.20%.