Compressed Fingerprint Matching and Camera Identification via Random Projections

Diego Valsesia, Giulio Coluccia, Tiziano Bianchi, Enrico Magli

IEEE Transactions on Information Forensics and Security, vol.10, no.7, pp.1472,1485, July 2015


Sensor imperfections in the form of photo-response nonuniformity (PRNU) patterns are a well-established fingerprinting technique to link pictures to the camera sensors that acquired them. The noise-like characteristics of the PRNU pattern make it a difficult object to compress, thus hindering many interesting applications that would require storage of a large number of fingerprints or transmission over a bandlimited channel for real-time camera matching. In this paper, we propose to use realvalued or binary random projections to effectively compress the fingerprints at a small cost in terms of matching accuracy. The performance of randomly projected fingerprints is analyzed from a theoretical standpoint and experimentally verified on databases of real photographs. Practical issues concerning the complexity of implementing random projections are also addressed by using circulant matrices.

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Poster @ IEEE WIFS 2015