Abstract
Biometric authentication technology identifies people by their unique biological information. An account holder’s body characteristics or behaviors are registered in a database and then compared with others who may try to access that account to see if the attempt is legitimate. Since veins are internal to the human body, its information is hard to duplicate. Compared with a finger or the back of a hand, a palm has a broader and more complicated vascular pattern and thus contains a wealth of differentiating features for personal identification. However, a single biometric is not sufficient to meet the variety of requirements, including matching performance imposed by several large-scale authentication systems. Multi-modal biometric systems seek to alleviate some of the drawbacks encountered by uni-modal biometric systems by consolidating the evidence presented by multiple biometric traits/sources. This paper proposes a multi-modal authentication technique based on Palm Veins as a personal identifying factor, augmented by face features to increase the accuracy of security recognition. The obtained results point at an increased authentication accuracy.
Highlights
Biometrics is automated methods of recognizing a person based on a physiological or behavioral characteristic
For palm veins, and according to Fig. 6, it is clear that the Moment Invariants method gives the best recognition rate for all types of noise
For evaluating the performance of the proposed system, we calculated the recognition rate for palm veins images corrupted by salt & pepper noise with intensities of 0, 15, 20, and 25% respectively
Summary
Biometrics is automated methods of recognizing a person based on a physiological or behavioral characteristic. It is not easy to determine which method of biometric data gathering and reading does the "best" job of ensuring secure authentication. Vein pattern recognition requires just a scan of the palm, making it the easiest and most natural to use among the various biometric technologies [2]. In addition to enhanced security, vein authentication used in conjunction with face recognition systems would keep a log of facial information should it be necessary to be used as evidence [3]. This paper proposes a bi-modal biometric authentication system that fuses the features of the palm veins with that of the face for increasing authentication accuracy. 4 types of statistical features are tested for the best recognition accuracy for palm veins and face independently. The paper is terminated by a conclusion summarizing the obtained results and specifying problems for future work
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