Abstract
Fingerprint recognition is widely used in security systems to recognize humans. In both industry and scientific literature, many fingerprint identification systems were developed using different techniques and approaches. Although the number of conducted research works in this field, developed systems suffer for some limitations partially those related the real time computation and fingerprint recognition. Accordingly, this paper proposes a reliable algorithm for fingerprint recognition based on the extraction and matching of Minutiae. In this paper, we present also an accelerated architecture based on GPU and multi-processor design in which the suggested fingerprint recognition algorithm is implemented.
Highlights
Individual identification presents a challenge for the modern society
The objective of this work is the development of a new accelerated architecture based on GPU and multi-processor design based on a new algorithm for fingerprint recognition based on the extraction and matching of Minutiae
This paper proposes, an architecture based on GPU and multi-processor design for fingerprint recognition to accelerate the identification time
Summary
Individual identification presents a challenge for the modern society. In this context, biometric recognition presents the most popular method for identification. Fingerprints are rich in details and contain a different form based on ridges. These forms define many characteristics point named ―Minutia‖. Each individual has unique repartition of Minutia which is different than others. Minutia is defined as a local ridge characteristic. Fingerprint contains various types of Minutia, but usually two types of Minutiae are used: Termination and Bifurcation. Termination is defined as the end point of a ridge. Bifurcation is defined as the point where a ridge merges or splits into branch ridges [1]
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