# A Survey on Robust Video Watermarking Algorithms for Copyright Protection
## 4 Robust Watermarking Algorithms Based on Original Videos
### Video Watermarking in Transform Domain
#### 4.2.3 SVD-Based Watermarking Algorithms  
SVD is a special matrix transformation, which can transform a matrix to two orthogonal matrices and one diagonal matrix with singular values. From the perspective of image processing, the singular value of images has good stability, and it embodies the intrinsic characteristics of images rather than the visual characteristics. These characteristics of SVD make it widely used in the field of robust video watermarking, and the watermark information is often embedded in the singular values matrix to get good imperceptibility [53]. Usually, it is adopted together with DWT in robust video watermarking [54; 55; 56; 57; 58; 59; 60]. In a past paper [54], a fast gradient magnitude similarity deviation (GMSD) algorithm was used to detect the shot boundaries of the video sequence, and then representative key-frames can be extracted. After the watermark information is encrypted by a new chaotic encryption, DWT and SVD are combined to embed the watermark information into extracted key-frames. [PERSON] and [PERSON] [55] also proposed a blind video watermarking algorithm based on a hybrid SVD/DWT technique. DWT is applied to the G components of selected frames, and then the obtained diagonal detail coefficients are implemented with SVD to embed watermark information into singular values matrices. To obtain high robustness with low payload, four kinds of embedding methods were proposed and compared in another past paper [56]. The fourth method, which combines the scene change detection and the spread spectrum approach, inserts only single watermark in the whole video, achieving the lowest payload but strong robustness. [PERSON] and [PERSON] [57] extracted key frames by scene change detection based on histogram difference method combining with the Fibonacci sequence. Before embedding, the watermark is scrambled by Fibonacci-Lucas transform to improve the security of the algorithm. The encrypted watermark is divided into blocks and embedded into the selected key frames based on the DWT and SVD. [PERSON] and [PERSON] [58] decomposed the color watermark image into 24-bit planes and scrambled them by Arnold transform before embedding. Contourlet transform (CT) is used to capture smooth contours in video frames selected by scene change detection, and DWT is used to obtain better multiresolution sub-bands. Then, SVD is implemented to select DWT sub-bands to embed the watermark. In a past paper [59], the selection of key frames was realized by chaotic map. DWT is performed on selected video frames, and SVD is performed on the transformed frames and watermark image, respectively. The two obtained singular value matrices are added to complete the watermark embedding. The algorithm proposed by [PERSON] and [PERSON] [60] takes all video frames as processing objects. DWT is adopted to luminance components of video frames, and 2-level DWT is implemented to the LH sub-bands. SVD is performed on the obtained HL\({}_{2}\) sub-bands using its high stability, and then watermark embedding can be realized. Hybrid DWT-SVD algorithms can not only have higher relevancy to human perception, but also reduce the dimension of data, which means that they can combine the advantages of DWT and SVD. However, using SVD of watermark image in embedding phase will lead to false positive detection problems [61]. The summary comparison of several SVD-based watermarking algorithms is shown in Table 5.