A compact representation of sensor fingerprint for camera identification and fingerprint matching
conference contribution
posted on 2015-01-01, 00:00 authored by R Li, Chang-Tsun LiChang-Tsun Li, Y Guan© 2015 IEEE. Sensor Pattern Noise (SPN) has been proved as an effective fingerprint of imaging devices to link pictures to the cameras that acquired them. In practice, forensic investigators usually extract this camera fingerprint from large image block to improve the matching accuracy because large image blocks tend to contain more SPN information. As a result, camera fingerprints usually have a very high dimensionality. However, the high dimensionality of fingerprint will incur a costly computation in the matching phase, thus hindering many interesting applications which require an efficient real-time camera matching. To solve this problem, an effective feature extraction method based on PCA and LDA is proposed in this work to compress the dimensionality of camera fingerprint. Our experimental results show that the proposed feature extraction algorithm could greatly reduce the size of fingerprint and enhance the performance in term of Receiver Operating Characteristic (ROC) curve of several existing methods.
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Pagination
1777-1781Location
Brisbane, QueenslandPublisher DOI
Start date
2015-04-19End date
2015-04-24ISSN
1520-6149ISBN-13
9781467369978Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2015, IEEETitle of proceedings
ICASSP 2015 : Proceedings of the IEEE International Conference on Acoustics, Speech and SignalEvent
Acoustics, Speech and Signal Processing. International Conference (2015 : Brisbane, Queensland)Publisher
IEEEPlace of publication
Piscataway, N.J.Usage metrics
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