Image histogram: maiden findings of anti-spoofing contrivance for hand biometrics acquisition

Biometrics data are prone to spoofing activitiesespecially on its sensor levels where fake biometrics data can be generated to replicate genuine biometrics data. Fake biometrics are false biometrics data that resembles genuine biometrics characteristics. If fake biometrics is accepted by a biometrics system, the possibility of personal information and data to be stolen is high. The consequences lie in the uninvited access and communities may become insecure to use biometrics as authentication tool. Biometrics acquisition process with an added detection mechanism can help distinguish between genuine and fake biometrics data. It is possible by the use of near infrared (NIR) light during acquisition process because interaction between NIR light with human skin and fake biometrics are different; due to the living trait property possessed by human. This paper shares preliminary findings of image histogram for both genuine and fake biometrics images acquired by NIR illumination. Observation on the image histogram reveals that there are metamorphoses to the image properties that can be used to distinguish between genuine and fake biometrics data. The approach can be extended its usage as detection mechanism for other biometrics data as well. The main principal lies in the difference of image response between genuine and fake biometrics data acquired by the NIR illumination.