Invariant image watermark using Zernike moments

The paper introduces a robust image watermark based on an invariant image feature vector. Normalized Zernike moments of an image are used as the vector. The watermark is generated by modifying the vector. The watermark signal is designed with Zernike moments. The signal is added to the cover image in the spatial domain after the reconstruction process. We extract the feature vector from the modified image and use it as the watermark. The watermark is detected by comparing the computed Zernike moments of the test image and the given watermark vector. Rotation invariance is achieved by taking the magnitude of the Zernike moments. An image normalization method is used for scale and translation invariance. The robustness of the proposed method is demonstrated and tested using Stirmark 3.1. The test results show that our watermark is robust with respect to geometrical distortions and compression.

[1]  Alireza Khotanzad,et al.  Classification of invariant image representations using a neural network , 1990, IEEE Trans. Acoust. Speech Signal Process..

[2]  Roland T. Chin,et al.  On image analysis by the methods of moments , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[3]  Thierry Pun,et al.  Robust template matching for affine resistant image watermarks , 2000, IEEE Trans. Image Process..

[4]  Alireza Khotanzad,et al.  Invariant Image Recognition by Zernike Moments , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Robert B. McGhee,et al.  Aircraft Identification by Moment Invariants , 1977, IEEE Transactions on Computers.

[6]  Heung-Kyu Lee,et al.  Rotation-, scale-, and translation-invariant image watermark using higher order spectra , 2003 .

[7]  Demetri Psaltis,et al.  Image Normalization by Complex Moments , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Sushil K. Bhattacharjee,et al.  Towards second generation watermarking schemes , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[9]  Ahmed H. Tewfik,et al.  Image watermarking by moment invariants , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[10]  S. S. Reddi,et al.  Radial and Angular Moment Invariants for Image Identification , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Ahmed H. Tewfik,et al.  Geometric distortion correction through image normalization , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[12]  Ingemar J. Cox,et al.  Electronic watermarking: the first 50 years , 2001, 2001 IEEE Fourth Workshop on Multimedia Signal Processing (Cat. No.01TH8564).

[13]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[14]  Martin Kutter,et al.  Watermarking resistance to translation, rotation, and scaling , 1999, Other Conferences.

[15]  Markus G. Kuhn,et al.  Attacks on Copyright Marking Systems , 1998, Information Hiding.

[16]  von F. Zernike.  Beugungstheorie des schneidenver-fahrens und seiner verbesserten form, der phasenkontrastmethode , 1934 .

[17]  Jürgen Allmann,et al.  On the digital implementation of the rotation-invariant Fourier-Mellin transform , 1987 .

[18]  Nikolas P. Galatsanos,et al.  Affine transformation resistant watermarking based on image normalization , 2002, Proceedings. International Conference on Image Processing.

[19]  JEFFREY WOOD,et al.  Invariant pattern recognition: A review , 1996, Pattern Recognit..

[20]  Thierry Pun,et al.  Rotation, scale and translation invariant spread spectrum digital image watermarking , 1998, Signal Process..

[21]  Frank Hartung,et al.  Multimedia watermarking techniques , 1999, Proc. IEEE.

[22]  Ingemar J. Cox,et al.  Rotation, scale, and translation resilient watermarking for images , 2001, IEEE Trans. Image Process..

[23]  Jürgen Altmann,et al.  On the Digital Implementation of the Rotation-Invariant Fourier-Mellin Transform , 1987, J. Inf. Process. Cybern..

[24]  Anthony P. Reeves,et al.  Three-Dimensional Shape Analysis Using Moments and Fourier Descriptors , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Paulo J. G. Lisboa,et al.  Translation, rotation, and scale invariant pattern recognition by high-order neural networks and moment classifiers , 1992, IEEE Trans. Neural Networks.

[26]  M. Kutter.  Watermaking resisting to translation, rotation, and scaling , 1998 .

[27]  Matthew L. Miller.  Watermarking with dirty paper codes , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[28]  Miroslaw Pawlak,et al.  On the Accuracy of Zernike Moments for Image Analysis , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[29]  Shahram Shirani,et al.  A robust multimedia watermarking technique using Zernike transform , 2001, 2001 IEEE Fourth Workshop on Multimedia Signal Processing (Cat. No.01TH8564).

[30]  Jia-Guu Leu,et al.  Shape normalization through compacting , 1989, Pattern Recognit. Lett..