Indexing and retrieving in fingerprint databases under structural distortions

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.

► We propose new fingerprint representation based on minutiae triangles. ► Delaunay triangles and other redundant ones are used in this representation. ► Redundant triangles help to deal with the problem of missing and spurious minutiae. ► Robust fingerprint features are also used in the proposed indexing scheme. ► The retrieval step is based on clustering in the transformation space.