Abstract
This paper presents a new algorithm for fingerprint indexing, which is based on minutia triplets, and it is very tolerant to missing and spurious minutiae. In this sense, a novel representation for fingerprints is proposed by defining a triangle set based on extensions of Delaunay triangulations. Moreover, a set of robust features is used to build indices. Finally, a recovery method based on calculating the recommendation score is introduced, using a new similarity function between geometric transformations. Our proposal was tested on well known databases, showing that it outperforms most of the already reported methods, especially under conditions of distortions.
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