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Title: Fast camera fingerprint matching in very large databases
Authors: Taşpınar, Samet
Sencar, Hüsrev Taha
Bayram, Sevinç
Memon, Nasir
Keywords: Sensor noise
PRNU noise
camera fingerprint
composite fingerprint
fingerprint digests
Issue Date: 2017
Publisher: IEEE
Source: Taspinar, S., Sencar, H. T., Bayram, S., & Memon, N. (2017, September). Fast camera fingerprint matching in very large databases. In 2017 IEEE International Conference on Image Processing (ICIP) (pp. 4088-4092). IEEE.
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.
Description: 24th IEEE International Conference on Image Processing (2017 : Beijing; China)
ISBN: 978-1-5090-2175-8
ISSN: 1522-4880
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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