DocumentCode :
2827583
Title :
Image watermarking by moment invariants
Author :
Alghoniemy, Masoud ; Tewfik, Ahmed H.
Author_Institution :
Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA
Volume :
2
fYear :
2000
fDate :
10-13 Sept. 2000
Firstpage :
73
Abstract :
We present a novel technique for watermarking digital images based on its moments. The watermark is composed of the mean of several functions of the second and third order moments designed to be invariant to scaling and orthogonal transformations this has the advantage of making the watermark image dependent. The watermarked image is a linear combination of the original image and a weighted nonlinear transformation of the original. The weight is computed such that the mean of the watermarked image invariants is a predefined number. Watermark detection is as simple as computing the moment invariants of the received image. Our approach has a guaranteed visual transparency up to a contrast modification. The proposed algorithm has proved to be highly robust to all geometric manipulations, filtering, compression and small cropping which are performed as part of StirMark attacks as well as noise addition, both Gaussian and salt and pepper.
Keywords :
copy protection; data compression; image coding; security of data; Gaussian noise; StirMark attacks; algorithm; compression; contrast modification; digital image watermarking; filtering; geometric manipulations; image dependent watermark; moment invariants; orthogonal transformations; salt and pepper noise; second order moment; small cropping; third order moment; visual transparency; watermark detection; watermarked image invariants; weighted nonlinear transformation; Digital images; Ear; Filtering algorithms; Gaussian noise; Image coding; Noise robustness; Nonlinear distortion; Parameter estimation; Pattern recognition; Watermarking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC, Canada
ISSN :
1522-4880
Print_ISBN :
0-7803-6297-7
Type :
conf
DOI :
10.1109/ICIP.2000.899229
Filename :
899229
Link To Document :
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