An Intelligent Palm Vein-based Human Recognition Framework

Abstract

The work is about recognizing people based on the veins in their palms. In many cases, authentication is a major issue to reduce crime and eliminate the possibility of spoofing the originality, so palm-vein for human recognition is used. Palm veins are more difficult to forge than fingerprints and palm-prints because they are an internal biometric of living human bodies. Extrinsic biometrics, such as fingerprints, ears, iris, and palm print, are vulnerable to forgery attacks, putting users’ privacy and protection at risk. Due to the acquisition of live palms and the necessity of user approval, palm vein traits are difficult to forge or reproduce. Aging, as well as bruises, scars, and tattoos, seems to have little effect on palm vein identification. The main goal of the palm-vein-based human recognition scheme is recognition accuracy. The palm vein-based human recognition mechanism is divided into five modules. The first module is pre-processing, which involves determining the ROI of the palm. The second module is feature extraction, which uses the wave atom transform (WAT) method to extract the required feature of the palm vein. The third module is function randomization, in which the extracted feature is randomized using a user-specific secret key, preventing hacking. The fourth module is template creation, in which each template is produced for verification. The fifth module is the identification module, which determines whether or not a person is genuine or an imposter by comparing database values. The CASIA multispectral palm print database is used for this project.