Abstract
Fingerprint indexing is a process of pre-filtering the template database before matching. The most common features used for fingerprint indexing are based on minutiae triplets. In this paper, we investigated the indexing performance based on some commonly used features of minutiae triplets and proposed to combine these features with some novel features of minutiae triplets for fingerprint indexing. Experiments on FVC 2000 DB2a and 2002 DB1a show that the proposed indexing method can perform better than state-of-the-art schemes for full fingerprint indexing, meanwhile, experimental results on NIST SD 14 show that the performance is improved significantly after the new features are added to the feature space, and is fairly good even for partial fingerprint indexing.
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Zhou, W., Hu, J., Wang, S., Petersen, I., Bennamoun, M. (2014). Fingerprint Indexing Based on Combination of Novel Minutiae Triplet Features. In: Au, M.H., Carminati, B., Kuo, CC.J. (eds) Network and System Security. NSS 2015. Lecture Notes in Computer Science, vol 8792. Springer, Cham. https://doi.org/10.1007/978-3-319-11698-3_29
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DOI: https://doi.org/10.1007/978-3-319-11698-3_29
Publisher Name: Springer, Cham
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