International Journal of Computer Applications (0975 – 8887) Volume 71– No.13, May 2013 16 A Method for Watermarking in Digital Videos by using Hybrid Transforms and Edge Detection Satyanarayana Murty. P Research Scholar AU, COE, VISHAKAPATNAM Rajesh Kumar. P Department of ECE AU Engineering College VISHAKAPATNAM ABSTRACT An approach for three robust and semi-blind digital video watermarking algorithms has been proposed in this paper. These algorithms are based on hybrid transforms using the combination of Discrete Cosine Transform and Singular Value Decomposition (DCT- SVD), Discrete Wavelet Transform and Singular Value Decomposition (DWT-SVD) and Discrete Wavelet Transform, Discrete Cosine Transform and Singular Value Decomposition (DWT-DCT-SVD). The original video is divided to number of frames. On one frame, the three hybrid transform algorithms have been applied separately. The process is repeated for all the reaming frames. The performance of the proposed algorithms is evaluated with respect to imperceptibility and robustness. The results show that the proposed algorithms give a good Peak Signal to Noise Ratio (PSNR), however their performance varied with respect to robustness. Keywords Watermarking, DWT, DCT, SVD, Robustness, and Hybrid transforms, Edge Detection 1. INTRODUCTION Due to the rapid and extensive growth of network technology, digital information can now be distributed much faster and easier. It causes the condition of illegal copies and spread of copyright reserved information. So, to protect the copyright of multimedia information and to decrease the impulse to copy and spread copy right reserved multimedia information, there are immense technical challenges in discouraging unauthorized copying and distributing of digital information. Fortunately, digital watermarking has been proposed as a method to embed an invisible signal into multimedia data so as to attest the owner identification of the data and discourage the unauthorized copying and distributing of digital information. In digital image watermarking the inserted watermark should not degrade the visual perception of an original image. This information of digital data can be extracted later for ownership verification [1]. Digital watermarking can applied to a variety of fields like text, image, audio, video and software. A lot of techniques are available for protecting the copyrighted material. The first method for hiding watermarking is by directly changing original cover-media. The advantages are simple and fast calculated but cannot protect itself from varied signal processing attacking [2, 3]. The most of watermarking techniques embed the information data in the coefficients of transformation domain of the cover image, such as Fourier transformation, discrete cosine transformation, wavelet transformation and singular value decomposition etc. Image watermarking algorithms using Discrete Cosine Transform (DCT) [4], the data hiding capacity is high in spatial domain and frequency domain algorithms based on DCT, SVD. However, these algorithms are hardly robust against various attacks, prone to tamper and degrade the quality of the watermarked image. Hybrid domain transforms are also available in the literature DCT- SVD [5, 6, 7] and DWT-SVD [8-12]. Now a day‟s people are looking to authenticate their video content by using either individual transforms or hybrid transforms [13 - 22] also. In this paper, three semi-blind reference video watermarking algorithms DCT-SVD, DWT-SVD and DWT-DCT-SVD have been proposed. The rest of the paper is organized as follows: section 2 contains our proposed algorithms, while Section 3 provides experimental results and in section 4 conclusions and in Section 5 references. 2. PROPOSED ALGORITHMS The watermark embedding and extraction process has shown in figure 1. 2.1 Algorithm using DCT-SVD 2.1.1. Watermark Embedding Procedure The objective of this procedure is to embed the watermark into the cover or host video without degrading the original host video. Step 1: Divide the video scene into frames  , i = 1, 2, 3…………n. Step 2: Convert every video frame   from RGB to     color matrix format. Step 3: Compute the steps 4 to 13 on the Y matrix in each frame  . Step 4: The Y matrix is segmented into blocks of size p 1 × p 2 via ZIG_ZAG sequence denoted by F l , where l is the number of blocks. Step5: Find out the number of edges in each block. Step6: The numbers of edges in each block are stored in descending order. Then make a threshold on the number of edges in each block. Those blocks, which have number of edges greater than or equal to threshold, are considered as significant blocks and are used for making reference image,   which is a size of n × n.