Latent Fingerprint In the Wild (LFIW) Database

Latent fingerprints are among the most important and widely used evidence in crime scenes, digital forensics and law enforcement worldwide. Despite the number of advancements reported in recent works, we note that significant open issues such as independent benchmarking and lack of largescale evaluation databases for improving the algorithms are inadequately addressed. The available databases are mostly of semi-public nature, lack of acquisition in the wild environment, and post-processing pipelines. Moreover, they do not represent a realistic capture scenario similar to real crime scenes, to benchmark the robustness of the algorithms. Further, existing databases for latent fingerprint recognition do not have a large number of unique subjects/fingerprint instances or do not provide ground truth/reference fingerprint images to conduct a cross-comparison against the latent. We introduce a new wild large-scale latent fingerprint database: Latent Fingerprint In the Wild (LFIW) that includes five different acquisition scenarios: reference fingerprints from (1) optical and (2) capacitive sensors, (3) smartphone fingerprints, latent fingerprints captured from (4) wall surface, (5) Ipad surface, and (6) aluminium foil surface. This new database consists of 600 unique fingerprint instances captured in all above-mentioned settings. A total of 1200 reference fingerprints from optical and capacitive sensors, 600 fingerphotos from smartphones, and 4200 latent fingerprints from each of the 60 subjects were provided in this work. The dataset is constructed considering various age groups, equal representations of genders and backgrounds. The LFIW latent fingerprint database enables researches in developing, testing and publishing human recognition algorithms.