Digital Video Watermarking Based on 3D-Discrete Wavelet Transform Domain Sadik. A.M .Al-Taweel #1 , Putra, Sumari *2 , Hailiza Kamarulhaili School of Computer Sciences, Mathematical School, Universiti Sains Malaysia, Minden 11800, Penang, Malaysia #3 1 Sadik@cs.usm.my 3 hailiza@cs.usm.my 2 putras@cs.usm.my Abstract—One of the significant problems in video watermarking is the Geometric attacks. The DWT (discrete wavelet transform) domain is used for proposed a novel algorithm to place invisible watermark in a video frame based on a three-level DWT using Haar filter. The proposed algorithm is robust against JPEG compression, geometric attacks such as Downscaling, Cropping, and Rotation. It is also robust against Image processing attacks such as low pass filtering (LPF), Median filtering, and Weiner filtering. Furthermore, the algorithm is robust against Noise attacks such as Gaussian noise, Salt and Pepper attacks. The embedded data rate is high and robust. The experimental results show that the embedded watermark is robust and invisible. The watermark was successfully extracted from the video after various attacks. I. INTRODUCTION It is important for Digital watermarking to have digital data and multimedia, such as video, music, text, and image copyright protection because of network and multimedia techniques that easily copy. Digital watermarking is a general solution that can be used to identify illegal copying and ownership, authentication, or other applications by inserting information into the digital data in visible, or an invisible way [1]. In order for a watermark to be useful, it must be perceptually invisible and have robustness against a variety of possible attacks and image processing by those who seek to corsair the material [2], [,3]. There has been much emphasis on the robustness of watermarking against signal processing operations. However, it has become clear that a very small of the geometric distortions can prevent the detection of a watermark in many watermarking techniques. There are three advantages of using watermarking [4]. First, the watermark is embedded into the media content in an imperceptible way, so that the information embedded is hidden and the effect on the appearance and function of the work is invisible. Second, the watermark is embedded in the content of the data and it is supposed to survive even after encryption and decryption, convert from digital to analog, compression, change of file format, resizing, or cropping. Third, any changes made can be identified by checking the watermark because it is embedded in such away as to locate the modified parts and restore the original. One of the challenges in the video and image watermarking is the geometric manipulations of the watermarked data. It is known that a small amount of rotation or scaling can dramatically disable the receiver from detecting the watermark. Geometric transformations are yet to be solved because of their high computation complexity, implementation difficulties, and poor performance [5]. So, geometric manipulation will destroy the synchronization of the watermarking embedding and detection process. The detection of the watermark requires a synchronization step to locate the embedded watermark in the content. Some of the video watermarking techniques are based on the spread spectrum approach which targets the geometric distortions and operation in the 3D wavelet domain and BCH codes, and 3D interliving by incorporating an effective temporal synchronization technique [6], [ 7]. Reviews on many other techniques that transform the video watermarking into discrete wavelet transform domain to handle the geometric distortions, attacks, and applications can be found in [8], [9] . In [10], the proposed technique works in the space domain and it is robust against geometric transformations like image cropping and resizing. Serdean et al [11] Presented robust geometric attack techniques such as shift, rotation, scaling and cropping in the spatial domain by employing image registration techniques. The weakness of the existing algorithms includes the low bit rate of the watermark. Other published papers in this domain are Chan et al [12], the researchers presented a novel DWT-based video watermarking scheme with scrambled watermark and error correcting code. The scheme is robust against attacks such as frame dropping, frame averaging, and statistical analysis. Campisi et al [13] proposed perceptual mask, applied in the 3D DWT domain robust against MPEG2 and MPEG-4 compression, collusion and transcoding attacks. In [14] propose a robust mpeg video watermarking in wavelet domain which they embedded in two bands (LL and HH) and chosen attacks JPEG compression, resizing, adding Gaussian noise, low pass filtering. In [15] present a novel adaptive watermarking scheme based on error correction code and Human Visual System (HVS) in 3D-DWT domain. The proposed method is to resist signal processing attacks, Gaussian noise, and frame dropping. In [16] propose a method based on 3D wavelet transforms. In this method the original video frames are divided into 3D- block according to HVS properties. The proposed method is 2009 IEEE International Conference on Signal and Image Processing Applications 978-1-4244-5561-4/09/$26.00 ©2009 352