Fingerprint image scale estimation for forensic identification systems

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Tim Oblak, Jovana Videnovic, Haris Kupinic, Vitomir Struc, Peter Peer, Ziga Emersic

Published: 01 Jan 2025, Last Modified: 12 Nov 2025Int. J. Comput. Commun. Control 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: The large majority of modern software solutions intended for fingermark processing in a forensic context is heavily dependant on the correct image scaling. Fingermark images captured with digital cameras at a crime scene require the use of physical rulers or labels. While the resolution of a fingermark image can be calibrated manually by a forensic examiner in a lab, we propose an automated approach, which could be integrated directly into existing identification systems and would eliminate the need for human intervention. Our approach consists of a CNN regressor, which directly predicts the PPI of stochastically-sampled local patches based on the friction ridge information contained within. In a range of PPI between 500 and 1500, our method achieves a mean average error of around 24 PPI for fingerprint and fingermark images.