A New Method for Estimating the Primary Quantization Step of JPEG Double-Compression

Wang Jun-wen; Liu Guang-jie; Dai Yue-wei; Zhou Lin-na; Guo Yun-biao

doi:10.3724/SP.J.1146.2007.01968

Volume 31 Issue 4

Dec. 2010

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2009 > 31(4): 836-839

Wang Jun-wen, Liu Guang-jie, Dai Yue-wei, Zhou Lin-na, Guo Yun-biao. A New Method for Estimating the Primary Quantization Step of JPEG Double-Compression[J]. Journal of Electronics & Information Technology, 2009, 31(4): 836-839. doi: 10.3724/SP.J.1146.2007.01968

Citation:

Wang Jun-wen, Liu Guang-jie, Dai Yue-wei, Zhou Lin-na, Guo Yun-biao. A New Method for Estimating the Primary Quantization Step of JPEG Double-Compression[J]. Journal of Electronics & Information Technology, 2009, 31(4): 836-839. doi: 10.3724/SP.J.1146.2007.01968

Citation:

PDF( 258 KB)

A New Method for Estimating the Primary Quantization Step of JPEG Double-Compression

doi: 10.3724/SP.J.1146.2007.01968

Received Date: 2007-12-25
Rev Recd Date: 2008-05-12
Publish Date: 2009-04-19

Abstract

Abstract

This paper presents a method for estimating the primary quantization step of double compressed JPEG image. The method in accordance with the relationship between the two quantization steps contains three situations. When the primary quantization step is larger than the second quantization step, the histogram can be used to calculate directly. To resolve the issue of multi-value caused by Fourier spectrum analysis and the problem that the primary quantization step is the factor of the second quantization step, the uncompressed image can be approximated by narrowing the image by 98%. This method can resolve the problem that the primary quantization step is the factor of the second quantization step, and uses spectrum analysis to reduce the complexity. The experimental results show that this method has higher accuracy of the estimation.

FullText(HTML)

References(1)

References

Sencar H T and Memon Nasir. Overview of state-of-art indigital image forensics. Part of Indian Statistical InstitutePlatinum Jubilee Monograph series titled 'Statistical Scienceand Interdisciplinary Research,' World Scientific Press, 2008.[2]Luo Weiqi, Qu Zhenhua, Pan Feng, and Huang Jiwu. Asurvey of passive technology for digital image forensics[J].Front.Comute. Sci. China.2007, 1(2):166-179[3]Fan Z and de Queiroz R L. Identification of bitmapcompression history: JPEG detection and quantizerestimation[J].IEEE Trans. on Image Processing.2003, 12(2):230-235[4]Fridrich J, Goljan M, and Du R. Steganalysis based on JPEGcompatibility. Special session on Theoretical and PracticalIssues in Digital Watermarking and Data Hiding, MultimediaSystems and Applications IV, Denver, Co, USA, August19-24, 2001: 275-280.[5]Fridrich J, Goljan M, and Hogea D. Attacking the outguess.Proc. Multimedia and Security, Workshop at ACMMultimedia, Juan-les-Pins, France, December 6, 2002: 3-6.[6]Fridrich J, Goljan M, and Hogea D. Steganalysis of JPEGimages: Breaking the F5 algorithm. Proc. 5th InternationalWorkshop on Information Hiding, Noordwijkerhout, TheNederlands, October 7-9, 2002: 310-323.[7]Lukas J and Fridrich J. Estimation of primary quantizationmatrix in double compressed JPEG images. Proc. Of DFRWS,Cleveland, OH, USA, August 6-8, 2003: 67-84.[8]Popescu A and Farid H. Statistical tools for digital forensics.6th International Workshop on Information Hiding, Toronto,Canada, May, 2004: 128-147.[9]He J, Lin Z, Wang L, and Tang X. Detecting doctored JPEGimages via DCT coefficient analysis. Proc. of ECCV, Berlin,2006: 423-435.

Relative Articles

Supplements(0)

Cited By

Proportional views