@inproceedings{bfaf7a203311432a99886839d28c560c,
title = "Fast camera fingerprint matching in very large databases",
abstract = "Given a query image or video, or a known camera fingerprint, there is a lack of capabilities for fast identification of media, from a large repository of images and videos, that match the query fingerprint. This work introduces a new approach that improves the computation efficiency of pairwise camera fingerprint matching and incorporates group testing to make the search more effective. More specifically, we jointly leverage the individual strengths of composite fingerprints and fingerprint digests in a novel manner and design two methods that are superior to existing approaches. The results show that under very high-performance requirements, where the probability of correct identification is close to one with a false-positive rate of zero, the proposed search methods are 2-8 times faster than the state-of-art search methods.",
keywords = "Camera fingerprint, Composite fingerprint, Fingerprint digests, PRNU noise, Sensor noise",
author = "Samet Taspinar and Sencar, {Husrev T.} and Sevinc Bayram and Nasir Memon",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 24th IEEE International Conference on Image Processing, ICIP 2017 ; Conference date: 17-09-2017 Through 20-09-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ICIP.2017.8297051",
language = "English",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "4088--4092",
booktitle = "2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings",
address = "United States",
}