TY - GEN
T1 - A machine learning based scheme for double JPEG compression detection
AU - Chen, Chunhua
AU - Shi, Yun Q.
AU - Su, Wei
PY - 2008
Y1 - 2008
N2 - Double JPEG compression detection is of significance in digital forensics. We propose an effective machine learning based scheme to distinguish between double and single JPEG compressed images. Firstly, difference JPEG 2-D arrays, i.e., the difference between the magnitude of JPEG coefficient 2-D array of a given JPEG image and its shifted versions along various directions, are used to enhance double JPEG compression artifacts. Markov random process is then applied to modeling difference 2-D arrays so as to utilize the second-order statistics. In addition, a thresholding technique is used to reduce the size of the transition probability matrices, which characterize the Markov random processes. All elements of these matrices are collected as features for double JPEG compression detection. The support vector machine is employed as the classifier. Experiments have demonstrated that our proposed scheme has outperformed the prior arts.
AB - Double JPEG compression detection is of significance in digital forensics. We propose an effective machine learning based scheme to distinguish between double and single JPEG compressed images. Firstly, difference JPEG 2-D arrays, i.e., the difference between the magnitude of JPEG coefficient 2-D array of a given JPEG image and its shifted versions along various directions, are used to enhance double JPEG compression artifacts. Markov random process is then applied to modeling difference 2-D arrays so as to utilize the second-order statistics. In addition, a thresholding technique is used to reduce the size of the transition probability matrices, which characterize the Markov random processes. All elements of these matrices are collected as features for double JPEG compression detection. The support vector machine is employed as the classifier. Experiments have demonstrated that our proposed scheme has outperformed the prior arts.
UR - http://www.scopus.com/inward/record.url?scp=77955699524&partnerID=8YFLogxK
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U2 - 10.1109/icpr.2008.4761645
DO - 10.1109/icpr.2008.4761645
M3 - Conference contribution
AN - SCOPUS:77955699524
SN - 9781424421756
T3 - Proceedings - International Conference on Pattern Recognition
BT - 2008 19th International Conference on Pattern Recognition, ICPR 2008
PB - Institute of Electrical and Electronics Engineers Inc.
ER -