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Partial fingerprint identification for large databases

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Abstract

Nowadays, most fingerprint sensors capture partial fingerprint images. Incomplete, fragmentary, or partial fingerprint identification in large databases is an attractive research topic and is remained as an important and challenging problem. Accordingly, conventional fingerprint identification systems are not capable of providing convincing results. To overcome this problem, we need a fast and accurate identification strategy. In this context, fingerprint indexing is commonly used to speed up the identification process. This paper proposes a robust and fast identification system that combines two indexing algorithms. One of the indexing algorithms uses minutiae triplets, and the other uses orientation field (OF) to index and retrieve fingerprints. Furthermore, the proposal uses some partial fingerprint matching methods on final candidate list obtained from the indexing stage. The proposal is evaluated over two national institutes of standards and technology (NIST) datasets and four fingerprint verification competition (FVC) datasets leading to low identification times with no accuracy loss.

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Acknowledgements

The authors are indebted to the editor and the anonymous reviewers whose comments and suggestions helped us to improve the quality of the paper.

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Authors and Affiliations

  1. Department of Computer Engineering and Information Technology, Payame Noor University (PNU), Qeshm, Iran

    Javad Khodadoust

  2. Department of Electrical Engineering, Sadjad University of Technology, Mashhad, Iran

    Ali Mohammad Khodadoust

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  1. Javad Khodadoust
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  2. Ali Mohammad Khodadoust
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Correspondence to Javad Khodadoust.

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Khodadoust, J., Khodadoust, A.M. Partial fingerprint identification for large databases. Pattern Anal Applic 21, 19–34 (2018). https://doi.org/10.1007/s10044-017-0665-0

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