Abstract
Owner-ship protection and authorization of digital multimedia is of paramount importance. The availability of powerful tools for editing, lossless copying and transmission of digital multimedia (such as images) has compounded the problem. Image watermarking is an effective solution for the problem of authentication and protection of copyrighted image content. In this paper Discrete Wavelet Transform (DWT) based watermarking technique is proposed in which mean energy of the each of 32x32 block in the CH and CV subbands is calculated and range of coefficients that exceed the mean energy of the corresponding block are selected for watermark embedding. Watson Perceptual Distortion Control Model is considered to keep the Perceptual quality of the image. Genetic Programming (GP) delivers optimum watermarking level for the selected coefficients. Results show negligible difference between original and watermarked image demonstrating key feature of imperceptibility. The technique proves to be effective against a set of malicious attacks.
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References
Khan, A., Anwar, M.M., Abdul, M.: Automatic Visual Masking of a Digital Watermark Using Genetic Programming. International Journal of Knowledge Based and Intelligent Engineering Systems (KES) 9(1), 1–11 (2005)
Fan, Z., Zhang, H.: Wavelet Domain Watermarking Capacity analysis. In: Li, C.-S., Yeung, M.M. (eds.) Electronic Imaging and Multimedia Technology IV, Proceedings of the SPIE, vol. 5637, pp. 657–664 (2005)
Ziqiang, W., Sun, X., Zhang, D.: A Novel Watermarking Scheme Based on PSO Algorithm. In: Li, K., Fei, M., Irwin, G.W., Ma, S. (eds.) LSMS 2007. LNCS, vol. 4688, pp. 307–314. Springer, Heidelberg (2007)
Ganic, E., Ahmet, M.E.: A DFT based semi blind watermarking scheme for images. In: Security, Steganography and Watermarking of Multimedia Contents. Conference No.7, San Jose CA, ETATS-UNIS, vol. 5681, pp. 175–184 (2005)
Veysel, A., Latif, A.A., Ozturk, S.: DWT-SVD Based Image Watermarking Using Particle Swarm Optimizer. In: IEEE ICME (2008)
Zhu, S., Jianming, L.: A Novel Adaptive Watermarking scheme Based on Human Visual System and Particle Swarm Optimization. In: Bao, F., Li, H., Wang, G. (eds.) ISPEC 2009. LNCS, vol. 5451, pp. 136–146. Springer, Heidelberg (2009)
Vikas, S., Gupta, J.P.: Collusion Attack Resistant Watermarking Scheme for colored images using DCT. IAENG International Journal of Computer science, IJCS_34_2_02 34(2) (2007)
Nuyen, C.T., Ganesh, C., Hammel, S.E.: Advanced Techniques for signal and Image compression/Reconstruction with Wavelets. In: Chapter of the IEEE Signal Processing Society, Washington, DC, pp. 24–25 (1995)
Zhen, L., Lina, J.K., Andrew, B.W.: JPEG2000 Encoding with perceptual Distortion Conrol. IEEE Transactions on Image Processing 15(7), 1763–1777 (2006)
Usman, I., Khan, A.: BCH coding and intelligent watermark embedding: Employing both frequency and strength selection. Applied Soft Computing ASCOC-640, 1–12 (2009)
Berlin, S.: Visual Cryptography. LNCS. Springer, Heidelberg
Langelaar, G., Setyawan, I., Langendij, R.L.: Watermarking Digital image and video Data. IEEE Signal Magazine 17, 20–43 (2000)
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Jabeen, F., Jan, Z., Jaffar, A., Mirza, A.M. (2010). Energy Based Coefficient Selection for Digital Watermarking in Wavelet Domain. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds) Information Computing and Applications. ICICA 2010. Communications in Computer and Information Science, vol 106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16339-5_34
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DOI: https://doi.org/10.1007/978-3-642-16339-5_34
Publisher Name: Springer, Berlin, Heidelberg
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