Using of Finger-Knuckle-Print in biometric security systems

Recently, several biometric technologies are considered mature enough to be a new tool for security and Finger-Knuckle-Print (FKP) based person identification is one of these technologies. This technology provides a reliable, low cost and user-friendly viable solution for a range of access control applications. Also, their rich texture information offers one of the powerful means in personal identification. In this paper, we propose a multi-algorithmic based biometric system for person recognition using FKP images. Thus, to extract the FKPs features, both, the 1D Log-Gabor Filter (LGF) response and Local Binary Pattern (LBP) descriptor are employed. Finally, performance of each technique is determined individually and a fusion at matching score level is applied to develop a multimodal system. Experimental results show that FKP modalities yields the best performance for identifying persons and it is able to provide an excellent identification rate and provide more security.

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