Image analysis – Applications
Reexamination Certificate
2006-02-28
2006-02-28
Au, Amelia M. (Department: 2623)
Image analysis
Applications
C382S166000, C382S244000, C713S176000
Reexamination Certificate
active
07006656
ABSTRACT:
Current methods of embedding hidden data in an image inevitably distort the original image by noise. This distortion cannot generally be removed completely because of quantization, bit-replacement, or truncation at the grayscales 0 and 255. The distortion, though often small, may make the original image unacceptable for medical applications, or for military and law enforcement applications where an image must be inspected under unusual viewing conditions (e.g., after filtering or extreme zoom). The present invention provides high-capacity embedding of data that is lossless (or distortion-free) because, after embedded information is extracted from a cover image, we revert to an exact copy of the original image before the embedding took place. This new technique is a powerful tool for a variety of tasks, including lossless robust watermarking, lossless authentication with fragile watermarks, and steganalysis. The technique is applicable to raw, uncompressed formats (e.g., BMP, PCX, PGM, RAS, etc.), lossy image formats (JPEG, JPEG2000, wavelet), and palette formats (GIF, PNG).
REFERENCES:
patent: 6047374 (2000-04-01), Barton
patent: 6633652 (2003-10-01), Donescu
patent: 6674873 (2004-01-01), Donescu et al.
patent: 6763121 (2004-07-01), Shaked et al.
patent: 2002/0146123 (2002-10-01), Tian
Zhu, B. et al., “Media Compression via Data Hiding,” IEEE Proc. 31stAsilomar Conf. on Signals, Systems and Computers, Nov. 1997, pp. 647-651.
Invertible Authentication, Jessica Fridrich.
Lossless Multiresolution Transform for Image Authenticating Watermarking, Benoit Marcq.
Invertible Authentication Watermark for JPEG Images, Jessica Fridrich.
Distortion-Free Data Embedding for Images, Miroslave Goljan.
Du Rui
Fridrich Jessica
Goljan Miroslav
Au Amelia M.
Mackowey Anthony
Milde & Hoffberg LLP
The Research Foundation of SUNY
LandOfFree
Lossless embedding of data in digital objects does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Lossless embedding of data in digital objects, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Lossless embedding of data in digital objects will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3657119