Author : Farhan A. Alenizi
Publisher :
ISBN 13 : 9780355307733
Total Pages : 145 pages
Book Rating : 4.3/5 (77 download)
Book Synopsis Robust Data Hiding in Multimedia for Authentication and Ownership Protection by : Farhan A. Alenizi
Download or read book Robust Data Hiding in Multimedia for Authentication and Ownership Protection written by Farhan A. Alenizi and published by . This book was released on 2017 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Establishing robust and blind data hiding techniques in multimedia is very important for authentication, ownership protection and security. The multimedia being used may include images, videos and 3D mesh objects.A hybrid pyramid Discrete-Wavelet-Transform (DWT) Singular-Value-Decomposition (SVD) data hiding scheme for video authentication and ownership protection is proposed. The data being hidden will be in the shape of a main color logo image watermark and another secondary Black and White (B&W) logo image. The color watermark will be decomposed to Bit-Slices. A pyramid transform is performed on the Y-frames of a video stream resulting in error images; then, a Discrete Wavelet Transform (DWT) process is implemented using orthonormal lter banks on these error images, and the Bit-Slices watermarks are inserted in one or more of the resulting subbands in a way that is fully controlled by the owner; then, the watermarked video is reconstructed. SVD will be performed on the color watermark Bit-Slices. A secondary B&W watermark will be inserted in the main color watermark using another SVD process. The reconstruction was perfect without attacks, while the average Bit-Error-Rates (BER's) achieved under attacks are in the limits of 2% for the color watermark and 5% for the secondary watermark; meanwhile, the mean Peak Signal-to-Noise Ratio (PSNR) is 57 dB. Furthermore, a selective denoising lter to eliminate the noise in video frames is proposed; and the performance with data hiding is evaluated.Moreover, a 3D mesh blind optimized watermarking technique is proposed in this research. The technique relies on the displacement process of the vertices locations depending on the modication of the variances of the vertices's norms. Statistical analysis were performed to establish the proper distributions that best t each mesh, and hence establishing the bins sizes. Experimental results showed that the approach is robust in terms of both the perceptual and the quantitative qualities.In conclusion, the degree of robustness and security of the proposed techniques are shown. Also the schemes that can be adopted to further enhance the performance, and the future work that can be done in the eld are introduced.