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Latent fingerprint identification is attracting increasing interest because of its important role in law enforcement. Although the use of various fingerprint features might be required for successful latent fingerprint identification, methods based on minutiae are often readily applicable and commonly outperform other methods. However, there exist many fingerprint feature representations, and we want to determine if the selection of a feature representation has an impact on the performance of an automated fingerprint identification system. In this paper, we review the most prominent fingerprint feature representations reported in the literature, identify trends in fingerprint feature representation, and observe that representations designed for verification are commonly used in latent fingerprint identification.We aim to evaluate the performance of the most popular fingerprint feature representations over a common latent fingerprint database and protocol. Therefore, we introduce and apply a protocol that evaluates some of the most suitable feature representations for latent fingerprint identification in terms of the area under either of two curves, i.e., DET and CMC, as well as in terms of the weighted Rank..20 identification rate.

A Review of Fingerprint Feature Representations and Their Applications for Latent Fingerprint Identification: Trends and Evaluation