Large-scale image retrieval based on compressed camera identification

Diego Valsesia, Giulio Coluccia, Tiziano Bianchi, Enrico Magli

to appear in IEEE Transactions on Multimedia, 2015.


Retrieving pictures from large collections according to a specific criterion is an increasingly relevant task. An important, but so far overlooked, such criterion is the retrieval of pictures acquired by a specific camera. Instead of relying on metadata, which can be absent or easily manipulated, a forensic tool is exploited, namely the Photo Response Non-Uniformity (PRNU) of the camera sensor. Recent works showed that random projections can be used to significantly compress the PRNU, enabling operation on very large scales, previously impossible due to the size of the PRNU and to the complexity of the matching operations. In this paper, we propose efficient techniques for management and retrieval of images employing the PRNU, and test them on a database of 1174 cameras and half a million pictures downloaded from the Internet.

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