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Special point representations for reducing data space requirements of finger-vein recognition applications

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Abstract

Due to the uniqueness of the finger-vein patterns hidden beneath the skin, forgery is very difficult. Providing fast and accurate finger-vein recognition represents the answer to biometric security system as we need more secure and reliable authentication methods. However, the finger-vein based recognition system is limited by the storage space and time complexity, which significantly reduce the accuracy of the identification. In this paper, we present an effective method of matching in a finger-vein recognition system to overcome the disadvantage of requiring significant data storage and heavy CPU computation requirements. Our proposed solution involved considering special points characterizing complex finger-vein information and their connections, thereby retaining only the evidence related to matching to perform subsequent identification. Experimental results show that our method achieves robust matching with an error rate of 0.216 % and confirm that the proposed mechanism can reduce the quantity of data that requires storage and maintain a certain level of authentication accuracy.

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Correspondence to Bo-Chao Cheng.

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Cheng, YC., Chen, H. & Cheng, BC. Special point representations for reducing data space requirements of finger-vein recognition applications. Multimed Tools Appl 76, 11251–11271 (2017). https://doi.org/10.1007/s11042-016-3300-y

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  • DOI: https://doi.org/10.1007/s11042-016-3300-y

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