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Hybrid video watermarking technique by using dwt & pca


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  • 1. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN INTERNATIONAL JOURNAL OF ELECTRONICS AND 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEMECOMMUNICATION ENGINEERING & TECHNOLOGY (IJECET)ISSN 0976 – 6464(Print)ISSN 0976 – 6472(Online)Volume 4, Issue 2, March – April, 2013, pp. 172-179 IJECET© IAEME: Impact Factor (2013): 5.8896 (Calculated by GISI) © HYBRID VIDEO WATERMARKING TECHNIQUE BY USING DWT & PCA 1 Mr. N. R. Bamane, 2Dr. Mrs. S. B. Patil , 3Prof. B. S. Patil, 4Prof. R. K. Undegaonkar 1 Dr. JJMCOE, JSP. 2 Head, Department of Electronics Engg. Dr. JJMCOE, JSP. 3 Head, Department of Information Technology PVPIT Budhgaon, Sangli 4 Trinity College of Engineering & research, Pune ABSTRACT Security and copyright protection are becoming important issues in multimedia applications and services, as Past few years have witnessed rapid growth in Digital video watermarking. Watermarking techniques have been proposed for these purposes in which the copyright information is embedded into multimedia data in order to protect the ownership. This paper presents a novel technique for embedding a binary logo watermark into video frames. The proposed scheme is an imperceptible and a robust hybrid video watermarking scheme. PCA is applied to each block of the two bands (LL – HH) which result from Discrete Wavelet transform of every video frame. The watermark is embedded into the principal components of the LL blocks and HH blocks in different ways. In this paper, a comprehensive approach for digital video watermarking is introduced, where a binary watermark image is embedded into the video frames. The proposed scheme is tested using a number of video sequences. Experimental results show high imperceptibility where there is no noticeable difference between the watermarked video frames and the original frames. Combining the two transforms improved the performance of the watermark algorithm. The scheme can be tested by applying various attacks. Keywords- Digital Video Watermarking, Copyright protection, Discrete wavelet transform, Principal component analysis, Binary logo watermark. 172
  • 2. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME1. INTRODUCTION Recently, the users of networks, especially the world wide web are increasing rapidly.The reproduction, manipulation and the distribution of digital multimedia (images, audio andvideo) via networks become faster and easier. Hence, the owners and creators of the digitalproducts are concerned about illegal copying of their products. As a result, security andcopyright protection are becoming important issues in multimedia applications and services.In the Past years, Watermarking techniques have been proposed for these purposes in whichthe copyright information is embedded into multimedia data in order to protect theownership. Research is now being focused on watermarking schemes to protect multimediacontent. Digital watermarking is a technology that can serve this purpose. A large number ofwatermarking schemes have been proposed to hide copyright marks and other information indigital images, video, audio and other multimedia objects. In the literature, different digital video watermarking algorithms have been proposed.Some techniques embed watermark in the spatial domain by modifying the pixel values ineach frame but these methods are not robust to attacks and common signal distortions. Incontrast, other techniques are more robust to distortions when they add the watermark in thefrequency domain. In these types of schemes, the watermark is embedded by modifying thetransform coefficients of the frames of the video sequence. The most commonly usedtransforms are the Discrete Fourier Transform (DFT), the Discrete Cosine Transform (DCT),and the Discrete Wavelet Transform. (DWT). Several researches concentrated on using DWTbecause of its multire solution characteristics, it provides both spatial and frequency domaincharacteristics so it is compatible with the Human Visual System (HVS). The recent trend is to combine the DWT with other algorithms to increase robustnessand invisibility. In this paper, we propose an imperceptible and robust video watermarkingalgorithm based on DWT and PCA. DWT is more computationally efficient than othertransform methods because of its excellent localization properties which provide thecompatibility with the Human Visual System (HVS). This paper is organized as follows:section 2 presents the proposed watermarking scheme. Section 3 introduces the experimentalresults and the conclusion is given in section 4.2. PROPOSED VIDEO WATERMARKING TECHNIQUE The proposed hybrid watermarking scheme is based on combining twotransformations; the DWT and the PCA. The block diagrams of embedding algorithms areshown in Fig.2. In our method, video frames are taken as the input, and watermark isembedded in each frame by altering the wavelet coefficients of selected DWT sub bands,followed by performing the PCA transformation on the selected sub bands.2.1 DISCRETE WAVELET TRANSFORM The DWT is used in a wide variety of signal processing applications. 2-D discretewavelet transform (DWT) decomposes an image or a video frame into sub images, 3 detailsand 1 approximation. The approximation sub image is lower resolution approximation image(LL) however the details sub images are horizontal (HL), vertical (LH) and diagonal (HH)detail components. The process can then be repeated to compute multiple "scale" waveletdecomposition. The main advantage of the wavelet transform is its compatibility with amodel aspect of the HVS as compared to the FFT or DCT. This allows us to use higher 173
  • 3. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEMEenergy watermarks in regions that the HVS is known to be less sensitive, such as the highresolution detail bands. Embedding watermarks in these regions allow us to increase therobustness of our watermark without any visible impact on the image quality. In the proposedalgorithm, sub-bands LL and HH from resolution level 2 of the wavelet transform of theframe are chosen for the embedding process. The following fig.1 shows the selected DWTbands which used in our proposed algorithm. Fig. a fig. b Fig.1 DWT sub-bands in (a) level 1, (b) level 2.Embedding the watermark in low frequencies obtained by wavelet decomposition increasesthe robustness against attacks like filtering, lossy compression and geometric distortionswhile making the scheme more sensitive to contrast adjustment, gamma correction, andhistogram equalization. Embedding the watermark in high frequency sub-bands makes thewatermark more imperceptible while embedding in low frequencies makes it more robustagainst a variety of attacks.2.2 PRINCIPAL COMPONENT ANALYSIS PCA is an optimal unitary transformation that projects the data on a new coordinatesystem such that the greatest data variation data comes lies on the first principal component,the second greatest variation on the second principal component, and so on. Thistransformation Orthogonalizes the components of the input data vectors so that they arecompletely de-correlated. The resulting orthogonal components called (principalcomponents) are ordered such that most of the energy is concentrated into the first severalprincipal components. Due to the excellent energy compaction property, components thatcontribute the least variation in the data set are eliminated without much loss of information.Unlike other linear transformations, the PCA does not have a fixed set of basis functions butit has basis functions which depend on the data set. Fig.2. Watermark Embedding process. 174
  • 4. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME The PCA approach is applied to the transform coefficients of wavelet sub band Iθwhere θ represents (LL or HH) as shown in the following steps:Step1: The wavelet subband Iθ with NxN dimension is subdivided into nxn non overlappingblocks (the block size should be appropriate to the sub band size) where the number of blocksis given by k = NxN/nxn.Step 2: Each block in LL band can be processed by method1 and each block in HH band canbe processed by method2 as following:method 1: Consider each block like a vector; data vectors can be expressed as: Iθ =(Iθ1, Iθ2,Iθ3,……., Iθk)T , where vector Iθi represents block number i with n2 dimension.method 2: Each block can be considered as 2D array Bθ =( Bθ1, Bθ2, Bθ3,……., Bθk)T ,where array Bθi represents block number i with size nxn.Step 3: For each block, the covariance matrix Ci of the zero mean block A is calculated as:Ci = Ai AiT (1)where T denotes the matrix transpose operation, and A is defined by :method 1: for a vector block as Ai=E(Iθi –mi).method 2: for 2D array block as Ai=E(Bθi –mi).where mi is the mean of block and E denotes expectation operation.Step 4: Each block is transformed into PCA components by calculating the eigenvectors(basis function) corresponding to eigenvalues of the covariance matrix:Ci Ф = λi Ф (2)where Ф is the matrix of eigenvectors and λ is the matrix of eigenvalues defined for:method 1: for a vector block as Ф = (e1 ,e2 ,e3 ,…., enxn) and λi =(λ1, λ2, λ3,… λnxn).method 2: for 2D array block as Ф = (e1 ,e2 ,e3 ,…., en) and λi = (λ1, λ2, λ3,…… λn).Ф vectors are sorted in descending order according to λi , where ( λ1 ≥ λ2 ≥ λ3 ≥ …..≥ λn or(λnxn)). The matrix Ф is an orthogonal matrix called basis function of PCA (PCAeigenimages)Step 5: Calculate the PCA components of the block. The PCA transforms the correlatedblock into uncorrelated coefficients by taking the inner product of the block with the basisfunctions Ф: Yi = ФT Ai (3)where Yi is the PC block which represents the principle component of block i.Step 6: Apply inverse PCA on the modified PCA components to obtain the modified waveletcoefficients. The inversion can be performed by the equation: Ai = Ф Yi (4)2.3 WATERMARK EMBEDDING The proposed watermarking process shown in Fig. 2 is briefly described in thefollowing steps:Step 1: Divide video into frames and convert 2Nx2N RGB frames into YUV components.Step 2: For each frame, choose the luminance Y component and apply the DWT todecompose the Y frame into four multi-resolution sub bands NxN: LL , HL , LH , and HH .Step 3: Divide the two sub bands LL and HH into n x n non-overlapping blocks.Step 4: Apply PCA to each block in the chosen subbands LL by using method1 and HHby using method2Step 5: Convert the 32x32 binary watermark logo into a vector W = { w1, w2 , ……. ,w32x32} of 0s and 1s. 175
  • 5. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEMEStep 6: Embed the logo into LL and HH bands by different ways. For LL band, thewatermark bits are embedded with strength α1 into the first principle component of each PCblock Yi. From equation (3) , for the PC block Y1, Y2, Y3,……., Yk, we can define YI =(Y1(1), Y2(1), Y3(1),……., Yk(1))T and the embedding equation:YI = YI + α1 W (5)Step 7: For HH band, use two pseudorandom sequences (PNS); p0 and p1 with differentkeys k1 and k2 to embed the watermark bit w 0 and 1 respectively [10,11]. So, we canrepresent Wm as follows: (6) when bit w=0, embed p0 with strength α2 to the mid-band coefficient of PC block Yiand when bit w=1, embed p1 with strength α2 to the mid-band coefficients of PC block Yi .If YB includes the mid-band coefficients then the embedding equation isYB = YB + α2 Wm (7)Step 8: Apply inverse PCA on the modified PCA components of the two bands to obtain themodified wavelet coefficients.Step 9: Apply the inverse DWT to produce the watermarked luminance component of theframe. Then reconstruct the watermarked frame3. EXPERIMENTAL RESULTS A number of video sequences are used for testing the proposed scheme for examplethe foreman video sequence. For evaluating the performance of any watermarking system,Peak Signal to Noise Ratio (PSNR) is used as a common measure of the visual quality of thewatermarking system. To calculate the PSNR, first the Mean Square Error (MSE) betweenthe original and watermarked frame is computed as follows: Where M, N are the size of the frame, and I(i, j), I(i, j) are the pixel values at location(i, j) of the original and watermarked frames. Then, PSNR is defined as The luminance component of the first 100 frames of the foreman video sequence arewatermarked. The frame size is 256x256. The watermark is a binary image withsize 32x32. The original sampled frame and its corresponding watermarked frame are shownin Fig. 3. The measured PSNR is 44.0975 db and the watermarked frame appearsvisually identical to the original. The value of PSNR is constant over all the tested frameswhich means that the error between the original and watermarked frames is very low so highvisual quality is obtained. Fig. 4 shows the original watermark and the extracted watermarkfrom LL band and HH band where no attacks were applied. The measured value of NC is 1for both LL band and HH band, i.e. the extracted watermark is identical to the original andexact extraction is obtained. 176
  • 6. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME Fig. 3 (a) Original frame, (b) Watermarked frame (PSNR = 44.0975db). Fig.4. Binary logo Watermark Fig.5 GUI used to execute the Experiment. Experimental results show high imperceptibility where there is no noticeabledifference between the watermarked video frames and the original frames. Combining thetwo transforms improved the performance of the watermark algorithm. The scheme can betested by applying various attacks. To measure the robustness of our proposed scheme, the watermarked frame can besubjected to a variety of attacks such as gamma correction, contrast adjustment, histogramequalization, and jpeg compression.4. CONCLUSION A hybrid video watermarking scheme has been proposed in this paper. The algorithmis implemented using 2-level DWT in conjunction with PCA transform. This scheme isimperceptible and robust against several attacks. A binary watermark has been embedded intoLL and HH bands of level 2 of DWT block based PCA. The proposed scheme has a goodperformance compared with previous schemes. As a future work, embedding the watermarkinto higher levels of the wavelet transform will be investigated. Collecting othertransformations together to enhancement the performance of the proposed scheme againstgeometric attacks will be studded. 177
  • 7. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEMEREFERENCES[1] M. K. Thakur, V. Saxena, and J. P. Gupta, “A Performance analysis of objective videoquality metrics for digital video watermarking”, 3rd IEEE International Conference onComputer Science and Information Technology – ICCSIT ‘10, 9-11 July, 2010, pp.12-17,Chengdu, China.[2] S. Voloshynovskiy, S. Pereira, and T. Pun, “Watermark attacks”, Erlangen WatermarkingWorkshop 99, October 1999.[3] C.I. Podilchuk and E.J. Delp, “Digital watermarking: algorithms and applications”, IEEESignal Processing Magazine, Vol. 18, Issue 4, July 2001, pp. 33-46.[4] P.W. Chan, M.R Lyu, and R.T. Chin, “A Novel scheme for hybrid digital videowatermarking”, IEEE Transactions on Circuits and Systems For Video Technology, Vol. 15,No. 12, December 2005.[5] G. Doërr and J.L. Dugelay, “A guide tour of video watermarking”, Signal Processing:Image Commun., April 2003, Vol. 18, No. 4, pp. 263–282.[6] Y. R. Lin, H.Y. Huang and W.H Hsu, “An embedded watermark technique in video forcopyright protection”, 18th International Conference on Pattern Recognition – ICPR ‘06, 20-24 August 2006, pp. 795- 798, Hong Kong.[7] C.V. Serdean, M.A. Ambroze., M. Tomlinson, and J.G. Wade, “DWT based videowatermarking for copyright protection, invariant to geometrical attacks”, IEE on Vision,Image and Signal Processing, Vol. 150, Issue 1, 2003, pp. 51- 58.[8] R. Chandramouli and N. Memon, “Analysis of LSB based image steganographytechniques”, in Proceedings International Conference on Image Processing, 7-10 October,2001, Vol. 3, pp. 1019–1022,Thessaloniki, Greece.[9] G. Langelaar, I. Setyawan, and R. Lagendijk, “Watermarking digital image and videodata”, IEEE Signal Processing Magazine, Vol. 17, No. 9, September 2000, pp. 20– 43.[10] I. J. Cox, J. Kilian, F. T. Leighton and T. Shamoon, “Secure spread spectrumwatermarking for multimedia”, IEEE Transactions on Image Processing, Vol. 6, Issue 12,1997, pp. 1673-1687.[11] C.H. Li and S.S. Wang, “Transform-based watermarking for digital images and video”,International Conference on Consumer Electronics –ICCE ‘99, 22-24 June, 1999, LosAngeles, USA. [12] J. Hussein and A. Mohammed, "Robust video watermarking using multi-band wavelettransform", International Journal of Computer Science Issues, IJCSI, Vol. 6, Issue 1,November 2009, pp. 44-49.[13] T. D. Hien, Y.W. Chen, and Z. Nakao, “A robust digital watermarking technique basedon principal component analysis” International Journal of Computational Intelligence andApplications, Vol. 4, No. 2, 2004, pp. 138-192.[14] C.V. Serdean, M.A. Ambroze, M. Tomlinson and J.G. Wade, “DWT Based VideoWatermarking for Copyright Protection, Invariant to Geometrical Attacks”, Proceedings ofthe 3rd International Symposium on Communication Systems Networks and Digital SignalProcessing – CSNDSP02, Stafford, UK, 15-17 July 2002.[15] Maher Elarbi, Chokri Amar, Henri Nicolas, "Video Watermarking Based on NeuralNetworks", IEEE International Conference on Multimedia and Expo, ICME06, pp.1577-1580, 2006.[16] Yang Gaobo; Sun Xingming; Wang Xiaojing, " A Genetic Algorithm based VideoWatermarking in the DWT Domain", IEEE, Digital Object Identifier10.1109/ICCIAS.2006.295247, pp.1209-1212. 178
  • 8. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME[17] Maher Elarbi, M. Ben Amar, C. Nicolas, H. " A Video Watermarking Scheme Resistantto Geometric Transformations", IEEE International Conference on Image Processing,ICIP07, Vol. 5, pp 481– 484, 2007.[18] Thai Duy Hien, Yen-Wei Chen, Zensho Nakao," PCA Based Digital Watermarking",KES 2003, LNAI 2773, pp. 1427-1434, 2003.[19] Yavuz E., Telatar Z., “Digital Watermarking with PCA Based Reference Images”,ACIVS 2007, Springer-Verlag, Lecture Notes in Computer Science, 4678, pp.1014-1023,2007.[20] Xiangui Kang ,WenjunZeng ,and Jiwu Huang, " A Multi-band Wavelet WatermarkingScheme ", International Journal of Network Security ,Vol 6 ,No 2, pp. 121–126, Mar 2008.[21] G. B. Khatri and D. S. Chaudhari, “Digital Audio Watermarking Applications andTechniques”, International journal of Electronics and Communication Engineering &Technology (IJECET), Volume 4, Issue 2, 2013, pp. 109 - 115, ISSN Print: 0976- 6464,ISSN Online: 0976 –6472.[22] Fahd N. Al-Wesabi, Adnan Z. Alsakaf and Kulkarni U. Vasantrao, “A Zero TextWatermarking Algorithm Based on the Probabilistic Patterns for Content Authentication ofText Documents”, International journal of Computer Engineering & Technology (IJCET),Volume 4, Issue 1, 2013, pp. 284 - 300, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. 179