Method and apparatus for steganalysis for texture images

Image analysis – Image compression or coding

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C382S100000

Reexamination Certificate

active

07885470

ABSTRACT:
Embodiments of the invention are directed toward methods for steganalysis that improve the detection of steganography in texture images. The methods combine features extracted from the image spatial representation and from a block discrete cosine transform (BDCT) representation with multiple different block sizes (i.e., N×N) to improve detection of data hidden in texture images. Image data that is to undergo steganalysis can be provided to embodiments of the invention in at least one of spatial (pixel) and JPEG format. When JPEG format is provided, the image is first decompressed to spatial representation, from which the features are extracted when the block size is at least one 2×2, 4×4, and 16×16. When the block size is 8×8, the JPEG coefficients (JPEG quantized 8×8 BDCT coefficients) derived directly from the JPEG image are used to extract features. In addition, the method is also effective as a universal steganalyzer for both texture and smooth
on-texture images. Embodiments of the invention also (1) utilize moments of 1-D and 2-D characteristic functions; (2) Prediction-error; and (3) all wavelet subbands including the low-low subbands.

REFERENCES:
patent: 5778102 (1998-07-01), Sandford et al.
patent: 6192139 (2001-02-01), Tao
patent: 6831991 (2004-12-01), Fridrich et al.
patent: 7239717 (2007-07-01), Fridrich et al.
patent: 2007/0104325 (2007-05-01), Lee
Fridrich: Feature-based steganalysis for JPEG images and Its implications for future design of steganographic schemes, Springer-Verlag, pp. 67-81, 2004.
Xuan et al: “Steganalysis based on multiple features formed by statistical moments of wavelet characteristic function”, Spinger-Verlag, pp. 262-277, 2005.
Lyu et al: “Detecting hiding messages using higher-order statistics and support vector machines”, Lecture notes in computer science, 2003, Springer.
Harmsen et al: “Kernel Fisher discriminant for steganalysis of JPEG hiding methods”, ACM Multimedia and Security, 2005.
Sullivan et al: “Steganalysis for Markov cover data with application to images”, IEEE-IFS, 2006.
Jackson: “Detecting novel steganography with an anomaly-based strategy”, J. of Electronic images, 2004.
Ang et al, “Video compression makes big gains”, IEEE, 1991, pp. 16-19.
L. Barford et al.: “an Introduction to Wavelets” Sep. 1992, Hewlett Parkard (HPL-92-124) h- Instruments and Photonics Laboratory, XP002493744 p. 2, paragraph 2-p. 3, paragraph 1 p. 6, paragraph 1.
Wo 2006/0813386 A (Mak Aquisitions LLC [US]; Shi Yun-Qing [US]; Xuan Guorong [CN]) Aug. 3, 2006 p. 5, line 7-line 17.
Livens S et al: “Wavelets for texture analysis, an overview” Image Processing and Its Applications Sixth International Conference on , Dublin, Ireland Jul. 14-17, 1997, IEE, UK, vol. 2, Jul. 14, 1997, pp. 581-585, XP006508359 abstract.
Harmen: “Steganalysis of Additive Noise Modelable Information Hiding” Thesis, Rensselaer Polytechnic Institute, Troy, New York, USA, Apr. 1, 2003, pp. 1-49, XP003014096 p. 32, paragraph 3-p. 34, paragraph 1.
Siwei Lyu et al: “Detecting hidden messages using higher-order statistics and support vector machines” Information Hiding. 5Th International Workshop, IH 2002. Revised Papers (Lecture notes in Computer Science vol. 2578) Springer Verlag Berlin, Germany, 2002, pp. 340-354, XP002493743 p. 341, paragraph 2-paragraph 3.
The Written Opinion of the International Searching Authority issued on Sep. 15, 2008 in related international application Serial No. PCT/US2008/051384.
International Preliminary Report on Patentability issued in related International Application No. PCT/US2008/051384.
G. Xuan et al., “Steganalysis Based on Multiple Features Formed by Statistical Moments of Wavelet Characteristic Functions,”Information Hiding Workshop(IHW 05), Barcelona, Spain, Jun. 2005.
Y.Q. Shi et al., “Steganalysis Based on Moments of Characteristic Functions Using Wavelet Decomposition, Prediction-Error Image, and Neural Network,”IEEE International Conf. on Multimedia and Expo(ICME 05), Amsterdam, Netherlands, Jul. 2005.
C. Chen et al., “Statistical Moments Based Universal Steganalysis Using JPEG 2-D Array and 2-D Characteristic Function,”IEEE Int'l Conf. on Image Processing(ICIP 06), Atlanta, Georgia, Oct. 2006.
M. Weinberger et al., “LOCO-I: A Low Complexity Content-Based Lossless Image Compression Algorithm,”Proc. of IEEE Data Compression Conf., pp. 140-149, 1996.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Method and apparatus for steganalysis for texture images does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Method and apparatus for steganalysis for texture images, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method and apparatus for steganalysis for texture images will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-2644872

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.