Deakin University
Browse

File(s) under permanent embargo

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.

History

Pagination

1777-1781

Location

Brisbane, Queensland

Start date

2015-04-19

End date

2015-04-24

ISSN

1520-6149

ISBN-13

9781467369978

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2015, IEEE

Title of proceedings

ICASSP 2015 : Proceedings of the IEEE International Conference on Acoustics, Speech and Signal

Event

Acoustics, Speech and Signal Processing. International Conference (2015 : Brisbane, Queensland)

Publisher

IEEE

Place of publication

Piscataway, N.J.

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC