A Hybrid Model for Human Recognition System Using Hand Dorsum Geometry and Finger-Knuckle-Print

Abstract

This study focuses on developing an efficient person identification and recognition system using hand based biometrics for secured access control. In most of the previous works on hand-based recognition methods, mostly, the importance was not given to the top side of the hand, which is used in this model. Iin our previous work we have developed a Hand based biometric recognition system using the palm side of the hand. In which, all features were extracted only from the palm side of the hand. Also, in some of the earlier works, the palm side of the hand was used for recognition purpose. The reason behind the selection of palm side of the hand is, it is very easy to capture using a simple scanning device and we can extract the shape based features as well as the palm print from the same image. In this study, we address a new hybrid model for biometrics based human recognition system using the dorsum of hand and the finger knuckle print. Dorsum of hand (backside of hand or topside of hand) is the opposite side of the palm side of the hand. In this study, we highlight some of the advantages of using dorsum of hand for modeling a biometrics based human recognition system. This study proposes a new hybrid model biometric system using Dorsum of Hand. Both the finger knuckle print and hand shape features are proposed to be extracted from the single hand image acquired from a top mounted camera setup. We use some unique features that improve the accuracy of the recognition. Several more significant hand attributes that can be used to represent hand shape and improve the performance are examined. Effective algorithms were used in the process of extracting different kinds of salient features from the dorsum of hand image.