Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pores and Ridges: High-Resolution Fingerprint Matching Using Level 3 Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computing the scene of a crime
IEEE Spectrum
Proceedings of the on Multimedia and security
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Non-invasive high-resolution Chromatic White Light (CWL) measurement devices offer great potential for solving the challenge of latent fingerprints age determination. In this paper, we place 40 prints from different subjects on hard disk platters and capture them from three different indoor locations every week over 1.5 years, acquiring high-resolution time series (10 μm and 20 μm). In contrast to prior findings from Popa et al. (using glass substrates) we show that the ridge thickness of our very precise images does not significantly decrease over time (test goal 1). We furthermore show that pores exhibit a significant loss in contrast and contour, which might lead to the impression of becoming bigger and fewer (test goal 2). Computing the contrast based Binary Pixel aging feature (test goal 3), we observe very characteristic results, leading to the conclusion that the dominant aging property seems to be an overall loss of image contrast rather than a specific change of ridge thickness or pore size. Comparing our findings between three different indoor locations (test goal 4) and discussing them from a police point of view, we conclude that sweat composition, environmental influences and scan parameters have a significant impact on fingerprints long-term aging.