Background: Fingerprint FP biometrics have benefited from high-resolution smartphone image sensors, allowing remote acquisition of papillary patterns without physical contact 1. Beyond traditional scanners, social media images may contain latent biometric data recoverable for forensic investigation. Case reports confirm successful identification of suspects through FP in photographs 1, 2. Furthermore, digital FP from uncontrolled environments or video frames can be effective for Automated Fingerprint Identification Systems AFIS 3. Deep learning models further enable ridge reconstruction from low-quality samples 4. The rising exposure of these images requires a systematic evaluation of current evidence. Objective: To review the literature and forensic case reports in order to assess the technical feasibility and reliability of human identification using FP from unconventional digital sources. Methods: This review followed the PICO framework and PRISMA guidelines. An exploratory search was conducted in PubMed, ScienceDirect, Scopus, and IEEE Xplore using the keywords: "fingerprints", "photographs", "identification", and "AFIS". Inclusion criteria were peer-reviewed forensic case reports and studies on remote capture, minutiae extraction, and AFIS integration, written in English and available in full text. Non-peer-reviewed documents, editorials, reviews, duplicates, and other biometric modalities were excluded. Analysis focused on image processing and ridge reconstruction. Results: Forensic case reports confirm identification via unconventional sources, such as photos of handheld objects 1 and mobile images 2, providing sufficient quality for high-confidence AFIS hits 3. Success depends on frame selection and digital filters to preserve papillary structure despite lighting and perspective challenges 1, 5. Advanced processing and Convolutional Neural Networks CNNs transform photographic fragments into valid evidence meeting law enforcement standards 3, 4. Conclusions: Forensic practice is evolving with FP increasingly accessible through public digital records 1, 3. Advances in reconstruction allow accuracy levels compatible with forensic standards 3, 5. This highlights the need for standardized guidelines for handling biometric data from uncontrolled sources and increased awareness of privacy risks.
Nunes et al. (Thu,) studied this question.