Fast source camera identification using matching signs between query and reference fingerprints

Fast camera fingerprint search is an important issue for source camera identification in real-world applications. So far there has been little work done in this area. In this paper, we propose a novel fast search algorithm. We use global information derived from the relationship between the query fingerprint/digest and the reference fingerprints/digests in the database to guide fast search. This information can provide more accurate and robust clues for the selection of candidate matching database fingerprints. Because the quality of query fingerprints may degrade or vary in realistic applications, the construction of robust search clues is significant. To speed up the search process, we adopt a lookup table that is built on the separate-chaining hash table. The proposed algorithm has been tested using query images from real-world photos. Experiments demonstrate that our algorithm can well adapt to query fingerprints with different quality. It can achieve higher detection rates with lower computational cost than the traditional brute-force search algorithm and a pioneering fast search algorithm in literature.

[1]  Donald E. Knuth,et al.  The Art of Computer Programming, Vol. 3: Sorting and Searching , 1974 .

[2]  Roberto Caldelli,et al.  An analysis on attacker actions in fingerprint-copy attack in source camera identification , 2011, 2011 IEEE International Workshop on Information Forensics and Security.

[3]  C. Metz.  Basic principles of ROC analysis. , 1978, Seminars in nuclear medicine.

[4]  Jessica J. Fridrich,et al.  Managing a large database of camera fingerprints , 2010, Electronic Imaging.

[5]  Donald E. Knuth,et al.  The art of computer programming, volume 3: (2nd ed.) sorting and searching , 1998 .

[6]  Chang-Tsun Li,et al.  Color-Decoupled Photo Response Non-Uniformity for Digital Image Forensics , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[7]  Kannan Ramchandran,et al.  Spatially adaptive statistical modeling of wavelet image coefficients and its application to denoising , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[8]  Jessica J. Fridrich,et al.  Large scale test of sensor fingerprint camera identification , 2009, Electronic Imaging.

[9]  Donald Ervin Knuth,et al.  The Art of Computer Programming , 1968 .

[10]  Heung-Kyu Lee,et al.  Source camera identification from significant noise residual regions , 2010, 2010 IEEE International Conference on Image Processing.

[11]  Miroslav Goljan,et al.  Digital camera identification from sensor pattern noise , 2006, IEEE Transactions on Information Forensics and Security.

[12]  Heung-Kyu Lee,et al.  On classification of source cameras: A graph based approach , 2010, 2010 IEEE International Workshop on Information Forensics and Security.

[13]  Jessica J. Fridrich,et al.  Camera identification from cropped and scaled images , 2008, Electronic Imaging.

[14]  Rainer Böhme,et al.  Can we trust digital image forensics? , 2007, ACM Multimedia.

[15]  Miroslav Goljan,et al.  Digital Camera Identification from Images - Estimating False Acceptance Probability , 2008, IWDW.

[16]  Min Wu,et al.  Nonintrusive component forensics of visual sensors using output images , 2007, IEEE Transactions on Information Forensics and Security.

[17]  Gregory W. Corder,et al.  Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach , 2009 .

[18]  Jiwu Huang,et al.  Enhancing Source Camera Identification Performance With a Camera Reference Phase Sensor Pattern Noise , 2012, IEEE Transactions on Information Forensics and Security.

[19]  Husrev T. Sencar,et al.  A study of the robustness of PRNU-based camera identification , 2009, Electronic Imaging.

[20]  Vito Cappellini,et al.  Analysis of denoising filters for photo response non uniformity noise extraction in source camera identification , 2009, 2009 16th International Conference on Digital Signal Processing.

[21]  Chang-Tsun Li,et al.  Source Camera Identification Using Enhanced Sensor Pattern Noise , 2009, IEEE Transactions on Information Forensics and Security.

[22]  Nasir D. Memon,et al.  Efficient techniques for sensor fingerprint matching in large image and video databases , 2010, Electronic Imaging.

[23]  Yongjian Hu,et al.  Source Camera Identification Using Large Components of Sensor Pattern Noise , 2009, 2009 2nd International Conference on Computer Science and its Applications.

[24]  Mo Chen,et al.  Determining Image Origin and Integrity Using Sensor Noise , 2008, IEEE Transactions on Information Forensics and Security.