Towards a Better Understanding of the Performance of Latent Fingerprint Recognition in Realistic Forensic Conditions

This work studies the performance of a state-of-the-art fingerprint recognition technology, in several practical scenarios of interest in forensic casework. First, the differences in performance between manual and automatic minutiae extraction for latent fingerprints are presented. Then, automatic minutiae extraction is analyzed using three different types of fingerprints: latent, rolled and plain. The experiments are carried out using a database of latent finger marks and fingerprint impressions from real forensic cases. The results show high performance degradation in automatic minutiae extraction compared to manual extraction by human experts. Moreover, high degradation in performance on latent finger marks can be observed in comparison to fingerprint impressions.