Detecting Recompression of JPEG Images via Periodicity Analysis of Compression Artifacts for Tampering Detection

Due to the popularity of JPEG as an image compression standard, the ability to detect tampering in JPEG images has become increasingly important. Tampering of compressed images often involves recompression and tends to erase traces of tampering found in uncompressed images. In this paper, we present a new technique to discover traces caused by recompression. We assume all source images are in JPEG format and propose to formulate the periodic characteristics of JPEG images both in spatial and transform domains. Using theoretical analysis, we design a robust detection approach which is able to detect either block-aligned or misaligned recompression. Experimental results demonstrate the validity and effectiveness of the proposed approach, and also show it outperforms existing methods.

[1]  Jiwu Huang,et al.  A Novel Method for Detecting Cropped and Recompressed Image Block , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[2]  Ricardo L. de Queiroz,et al.  Identification of bitmap compression history: JPEG detection and quantizer estimation , 2003, IEEE Trans. Image Process..

[3]  Alex ChiChung Kot,et al.  Accurate detection of demosaicing regularity from output images , 2009, 2009 IEEE International Symposium on Circuits and Systems.

[4]  Hany Farid,et al.  Exposing digital forgeries by detecting traces of resampling , 2005 .

[5]  W. Marsden I and J , 2012 .

[6]  Junfeng He,et al.  Detecting Doctored JPEG Images Via DCT Coefficient Analysis , 2006, ECCV.

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

[8]  Chiou-Ting Hsu,et al.  Image tampering detection by blocking periodicity analysis in JPEG compressed images , 2008, 2008 IEEE 10th Workshop on Multimedia Signal Processing.

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

[10]  Min Wu,et al.  Intrinsic Sensor Noise Features for Forensic Analysis on Scanners and Scanned Images , 2009, IEEE Transactions on Information Forensics and Security.

[11]  Wei Su,et al.  A generalized Benford's law for JPEG coefficients and its applications in image forensics , 2007, Electronic Imaging.

[12]  Avideh Zakhor,et al.  Iterative procedures for reduction of blocking effects in transform image coding , 1991, Electronic Imaging.

[13]  Bin Li,et al.  Detecting doubly compressed JPEG images by using Mode Based First Digit Features , 2008, 2008 IEEE 10th Workshop on Multimedia Signal Processing.

[14]  Siwei Lyu,et al.  How realistic is photorealistic , 2005 .

[15]  Miroslav Goljan,et al.  Steganalysis based on JPEG compatibility , 2001, SPIE ITCom.

[16]  Sanjeeb Dash,et al.  JPEG compression history estimation for color images , 2003, IEEE Transactions on Image Processing.

[17]  Pin Zhang,et al.  Detecting Image Tampering Using Feature Fusion , 2009, 2009 International Conference on Availability, Reliability and Security.

[18]  Ee-Chien Chang,et al.  Detecting Digital Image Forgeries by Measuring Inconsistencies of Blocking Artifact , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[19]  Hany Farid,et al.  Exposing digital forgeries by detecting inconsistencies in lighting , 2005, MM&Sec '05.

[20]  Alin C. Popescu,et al.  Exposing digital forgeries in color filter array interpolated images , 2005, IEEE Transactions on Signal Processing.