Publications (4)0 Total impact
- Proc. IEEE International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP2012); 07/2012
- International Journal of Digital Crime and Forensics. 07/2012; 4(3):20-32.
Conference Proceeding: On classification of source cameras: A graph based approach[show abstract] [hide abstract]
ABSTRACT: Many existing source camera classification methods involve either training a classifier or computing the reference pattern noise of a camera, which means a set of images of known origins have to be pre-acquired. However, such requirement can not always be satisfied in real-world forensic applications. In this work, we propose a graph based approach that requires no extra auxiliary images nor a prior knowledge about the constitution of the image set. By formulating the classification task as a graph partitioning problem, a set of images can be classified according to their source cameras in an entirely blind way, with the number of source cameras automatically estimated. Experimental results have verified the validity of the proposed approach.Information Forensics and Security (WIFS), 2010 IEEE International Workshop on; 01/2011
Conference Proceeding: Source camera identification from significant noise residual regions[show abstract] [hide abstract]
ABSTRACT: This paper investigates the digital forensic problem of determining whether an image has been produced by a specific digital camera. We employ the binary hypothesis testing scheme to detect the presence of photo-response non-uniformity( PRNU) in the image. The main challenge of this scheme is the extremely weak amount of PRNU in the observed noise residual. We propose to extract from the noise residual the significant regions with higher signal quality and discard those regions heavily deteriorated by irrelevant noises. Experimental results demonstrate that the proposed algorithm can improve the identification performance in the sense of decreasing the false rejection rate, which is a critical measure in practical applications.Image Processing (ICIP), 2010 17th IEEE International Conference on; 10/2010