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.
Published Version
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