DocumentCode :
3150955
Title :
A two dimensional camera identification method based on image sensor noise
Author :
Chan, Lit-Hung ; Law, Ngai-Fong ; Siu, Wan-chi
Author_Institution :
Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Hong Kong, China
fYear :
2012
fDate :
25-30 March 2012
Firstpage :
1741
Lastpage :
1744
Abstract :
In this paper, we propose a two-dimensional digital camera identification method based on the photo-response non-uniformity (PRNU). The traditional identification method is based on a correlation estimator which calculates the correlation between the reference PRNU and the PRNU extracted from the testing image. However, the correlation calculated greatly depends on the image content. To reduce the image content effect in classification, a correlation predictor is trained based on different types of image features. By using the predicted correlation and the actual correlation, a 2D classifier using support vector machine is proposed in this paper. Experimental results show that the proposed method can have a more flexible threshold setting which gives a better identification results as compared to the traditional identification method.
Keywords :
cameras; correlation methods; image classification; image sensors; support vector machines; correlation estimator; correlation predictor; image classification; image content effect; image feature; image sensor noise; photo response nonuniformity; support vector machine; testing image; two dimensional camera identification method; two dimensional digital camera identification method; Abstracts; Correlation; Helium; Reliability theory; Camera identification; Digital Forensics; Photo-response non-uniformity (PRNU);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location :
Kyoto
ISSN :
1520-6149
Print_ISBN :
978-1-4673-0045-2
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2012.6288235
Filename :
6288235
Link To Document :
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