Abstract

Digital watermarking is the mechanism by which security is provided to the sensitive data which is stored in the databases in the form images. In this process, all the essential features of an image is extracted and calculated after which this original image is implanted into the watermark image. In this research paper, GLCM and PCA algorithm has been utilized in order to improve the working capability of the neural network based watermarking technique. Therefore, the features of the original images are extracted with the help of GLCM and PCA algorithm. The scaling factor defines the output of the PCA algorithm which is used for implementation. On the basis of simulation results it is concluded that proposed algorithm performs well in terms of PSRN and MSE and MATLAB tool is used for the implementation of the proposed method.

References

• Kashyap, Nikita, and G. R. Sinha. "Image watermarking using 3-level discrete wavelet transforms (DWT)." International Journal of Modern Education and Computer Science (IJMECS) 4.3 (2012): 50.
• T. Serre, L. Wolf, S. Bileschi, M. Riesenhuber, and T. Poggio, “Object recognition with cortex-like mechanisms,” IEEE Trans. on PAMI vol. 29, no. 3, 2007.
• J.-K. Kamarainen, V. Kyrki, and H. K ¨ alvi¨ ainen, “Invariance properties of Gabor filter based features - overview and applications,” IEEE Trans. on Image Processing, vol. 15, no. 5, pp. 1088–1099, 2006.
• D. Gabor, “Theory of communication,” Journal of Institution of Electrical Engineers, vol. 93, pp. 429–457, 1946.
• J. Ilonen, J.-K. Kamarainen, P. Paalanen, M. Hamouz, J. Kittler, and H. K¨ alvi¨ ainen, “Image feature localization by multiple hypothesis testing of Gabor features,” IEEE Trans. on Image Processing, vol. 17, no. 3, pp. 311–325, 2008
• Singh, Surya Pratap, Paresh Rawat, and Sudhir Agrawal, A robust watermarking approach using DCT-DWT, International Journal of Emerging Technology and Advanced Engineering (ISSN 2250-2459, Volume 2, Issue 8 (2012).
• Al-Haj, Ali, Combined DWT-DCT digital image watermarking, Journal of computer science 3, no. 9 (2007): 740.
• Mansouri, A., A. Mahmoudi Aznaveh, and F. Torkamani Azar. "SVD-based digital image watermarking using complex wavelet transform." Sadhana 34, no. 3 (2009): 393-406.
• Lu, Chun-Shien, and H-YM Liao. Multipurpose watermarking for image authentication and protection, Image Processing, IEEE Transactions on 10, no. 10 (2001): 1579-1592.
• Martin, Alberto, and Sabri Tosunoglu, Image processing techniques for machine vision, Miami, Florida (2000).
• Chaturvedi, Navnidhi, and S. J. Basha. Comparison of Digital Image watermarking Methods DWT & DWT-DCT on the Basis of PSNR, image 2 (2012): 1.
• D. Gabor, “Theory of communication,” Journal of Institution of Electrical Engineers, vol. 93, pp. 429–457, 1946.
• J. Ilonen, J.-K. Kamarainen, P. Paalanen, M. Hamouz, J. Kittler, and H. K¨ alvi¨ ainen, “Image feature localization by multiple hypothesis testing of Gabor features,” IEEE Trans. on Image Processing, vol. 17, no. 3, pp. 311–325, 2008.
• J. Ilonen, J.-K. Kamarainen, and H. K ¨ alvi¨ ainen, “Fast extraction of multi-resolution gabor features,” in 14th Int Conf on Image Analysis and Processing (ICIAP), 2007, pp. 481–486.
• E. Simoncelli, W. Freeman, E. Adelson, and D. Heeger, “Shiftable multiscale transforms,” IEEE Transactions on Information Theory, vol. 38,no. 2, pp. 587–607, 1992.