Index Mapping based Hybrid DWT-DCT Watermarking Technique for Copyright Protection of Videos Files

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1 15 Online International Conerence on Green Engineering and Technologies (IC-GET) Index Mapping based Hybrid DWT-DCT Watermarking Technique or Copyright Protection o Videos Files Alavi Kunhu, Nisi K, Sadeena Sabnam, Majida A Department o Electronics and Communication Engineering Cochin College o Engineering and Technology Valanchery, India alavi@cochincet.ac.in Abstract In this paper, we propose a new blind colour video watermarking technique or the copyright protection o multimedia colour videos using index mapping concept. The novelty in the presented approach consists in designing a hybrid Discrete Wavelet Transorm (DWT) and Discrete Cosine Transorm (DCT) based digital video watermarking o colour watermark logo using index mapping technique. The distortion caused by watermarking is assessed by using peak signal to noise ratio (PSNR) and similarity structure index measure (SSIM) and robustness against dierent types o attacks have been assessed using StirMark. The proposed video watermarking algorithm provides better imperceptibility in harmony with the human visual system and oers higher robustness against signal processing attacks. Keywords Video watermarking; Copyright protectio; discrete wavelet transorm; discrete cosine transorm; peak signal to noise ratio; similarity structure index measure. I. INTRODUCTION As a result o the rapid growth in the digital computer technology, or the last ew years there has been a large demand or video watermarking products due to the act that there are so many videos available at no cost on the World Wide Web, which need to be, copyright protected and ownership authenticated [1]. The protection o intellectual property rights and digital media has become in great demand. Thus, the best way to protect multimedia products against illegal transactions is through hiding inormation within the cover called digital watermarking. The use o digital watermark technology, which has become more convenient, depends on hiding watermark in a digital medium. The watermark is the inormation regarding the owner o a copyright or this digital media. This could be a brand image, a serial number or any other digital inormation that describes the copyright []. For this digital interace, a watermark and a digital interace can be merged to make it diicult to be separated rom each other. Whenever it is Saeed AL-Mansoori Applications Development and Analysis Center (ADAC) Mohammed Bin Rashid Space Center (MBRSC) Dubai, UAE saeed.almansoori@mbrsc.ae required to validate the copyright, the watermark is extracted rom the digital interace to prove their legal owner. The watermark must be robust against several attacks either intentional or non-intentional [3]. To be eective, a watermark needs to have certain eatures such as being imperceptible and undeletable. Any watermarking technique consists o an encoding algorithm which embeds the watermark inormation into the host cover and decoding algorithm to extract the watermark inormation rom watermarked cover [4]. The objective o this project is to develop a hybrid discrete wavelet transorm and discrete cosine transorm based video watermarking algorithm which embeds robust ownership watermark inormation into video rames to protect the copyright ownership II. REVIEW OF DWT AND DCT The proposed digital video watermarking algorithm is based on hybrid Discrete Wavelet Transorm (DWT) and Discrete Cosine Transorm (DCT). A brie review o DWT and DCT are described below. A. Best Hiding Location Selection Technique Fig. 1. Best hiding location o video rames

2 This proposed algorithm will select the best three watermark logo hiding locations or each video rames using DCT. Here irst the level DWT decomposed LL block o selected video rame layer is divided into non-overlapping 8x8 sub-blocks and ind out the D-DCT o each sub-block. For each sub-blocks the 16 lower requencies DCT coeicients are screened to ind the best three coeicients with highest magnitude and register their locations [4]. The best three locations which are repeated more are selected and the selected best three locations will vary rom one video rame to another according to the spatial requency contents o the video rame. Fig. 1 graphically shows the best 3 watermark hiding locations o various video rames. B. Discrete Wavelet Transorm (DWT) 15 Online International Conerence on Green Engineering and Technologies (IC-GET) DCT is a process o converting a signal rom spatial domain to requency domain. In the case o multimedia videos, by applying D-DCT each video rames are divided into three regions o requencies called low requencies subband (FL), middle requencies sub-band (FM) and high requencies sub-band (FH). Fig. 3 shows the regions o requency sub-bands in video rames blocks, while Fig. 4 shows the DCT energy distribution. As it can be seen the highest energy coeicients is concentrated on the let-top corner where the highest energy coeicient is called a DC component while other coeicients stand or AC components. Most o the signal energy lies at low-requencies sub-band which contains the most important visual parts o the video rames. In addition, the Human Visual System (HVS) is more sensitive to this region. 3 Discrete wavelet analysis, use the concept o approximations and details. The approximations are the highscale, low-requency components, which gives the signal its identity, while the details are the low-scale, high-requency components, which imparts lavor. In the proposed hybrid watermarking technique, the discrete wavelet transorm (DWT) decompose a video rame into a lower resolution approximation (LL) as well as horizontal (HL), vertical (LH) and diagonal (HH) detail components. This decomposition process can be repeated to compute multiple "scale" wavelet decomposition and levels DWT decomposition model is shown in Fig. [5, 6, 7]. Accurate aspects o the HVS is the one o main advantages o the wavelet transorm and this allows us to use higher energy watermarks in regions that the HVS is known to be less sensitive to, such as the high resolution detail bands {LH, HL, HH}. Embedding watermarks in these regions allow us to increase the robustness o our watermark, at little to no additional impact on video quality. LL LH HL HH HL Fig. 3. DCT requency sub bands Fig. 4. DCT Energy Spectrum Mathematically, the DCT transorm can be expressed as ollows: y( u, v) M uv N M 1N 1 u v where α u and α v are given by: 1/, u u 1, u 1,,..., N 1 1/, v v 1, v 1,,..., N 1 (m 1) u (n 1) v x( m, n) cos cos M N The Inverse DCT transorm can be expressed as ollows: x( m, n) M N M 1N u v, (m 1) u (n 1) v uv y( u, v) cos cos () M N (1) LHl HHl where x(m, n) is the pixel intensity o selected channel o video rame block in row and column and y(u,v) is the DCT transorm coeicients in row and column o the DCT block. Fig.. levels DWT decomposition model C. Discrete Cosine Transorm (DCT) III. PROPOSED METHODOLAG A. Watermark Encoding Algorithm The proposed robust encoding algorithm can embeds up to 8 colour index map colour ownership watermark logo into the colour video ile in hybrid requency and wavelet domain

3 using Index Mapping, DWT and DCT respectively. Each colour pixel o the logo will require the insertion o 3 bits in the hybrid DWT-DCT domain. First we need to convert the colour watermark logo into 3bit logo index using index mapping table shown in Table I. Then the colour video ile is converted into rames and transormed into RGB color space and selects a suitable channel or watermarking. Then -level DWT haar wavelet decomposition is applied to the selected channel to obtain the LL sub-band. Subsequently, the LL sub-band is divided into a non-overlapping (8 8) blocks and converted into a requency domain using DCT. Then, the index mapped ownership watermark inormation is embedded into a selected best three coeicients location selected using best hiding location selection algorithm using scaled odd/even embedding technique. The complete encoding algorithm is summarized in Algorithm 1, where k indicates video rame, l(x, represents the index mapped watermark inormation, Q e represents even quantization and Q o represents odd quantization to the nearest integer number. The symbol Δ indicates the watermark strength scaling actor. TABLE I. INDEX MAPPING TABLE FOR WATERMARK COLOUR LOGO Logo Colour Combinations Index Key Binary Value Blue 1 1 Green 1 ellow 3 11 Red 4 1 White Online International Conerence on Green Engineering and Technologies (IC-GET) or k= 1 to N HB do i lo(x, = then DLL k Qe DLL k (x, = DLL k else DLL k Qo DLL k (x, = DLL k end i B. Watermark Decoding Algorithm The decoding algorithm extracts the watermarked ownership colour logo inormation rom the DCT and Hash multi watermarked colour satellite image using the discrete cosine transorm (DCT). Here irst extract the logo index key using Odd/Even extraction technique and convert into watermark colour logo using index mapping table. DLL ( u, v) i Q k Even lr ( i, j) 1 Odd lr ( i, j) (3) (4) Algorithm 1: Embedding copyright watermark Initialize: DCT block size, Wavelet type, Scaling actor ( ) Input: Selected channel o video rame ( k ), Watermark inormation (lo) Output: Robust watermarked video rame (w k ) Finding -level DWT [LL 1, LH 1, HL 1, HH 1 ] = DWT[ k ] [LL, LH, HL, HH ] = DWT[LL 1 ] Finding DCT o N HB 8 8 sub-blocks o LL or k=1 to N HB do or i= 1 to 8 do or j= 1 to 8 do ind LL k sub-block o LL DLL k (u,v) = DCT {LL k (i,j)} Finding the best three hiding location Encoding Index mapped watermark inormation IV. RESULT ANALSIS The proposed DCT and Hash multi watermarking algorithm perormance is tested on various colour video iles. Examples are shown in Fig. 5 where each video rame is pixels and Fig. 6 shows pixels Khalia University color logos used as ownership watermark inormation. The dierent watermark strength scaling actors used are 8, 16 and 4. The distortion caused to the video images was assessed by using the peak signal to noise ratio (PSNR) and the structural similarity index measurement (SSIM), while the recovered watermark logo perormance under the various attacks were analyzed using the normalized correlation (NC). The Peak Signal-to-Noise Ratio (PSNR) and the Structural Similarity Index Measurement (SSIM) are used as metric to measure quality o video watermarked rames [9, 11], Meanwhile the Bit Error Rate (BER) and the Normalized Correlation (NC) are used as a metric to measure the quality o extracted watermark colour logo inormation rom the video rames.

4 15 Online International Conerence on Green Engineering and Technologies (IC-GET) Video1 rame Video rame Video rame Video4 rame Fig. 5. Colour Video rames L( o, A X B, C ( o, A X B X C S( o, C X X where o represents the original video rame and w represents a watermarked video rame. L, C and S represent the luminance, contrast and structure components respectively, while α, β, γ are parameters used to adjust the relative importance o the luminance, contrast and structure components. The Normalized Correlation (NC) is a metric used to analyze the perormance o the extracted watermark inormation. I both the original and the extracted watermark are the same, then the value o NC will be 1. NC is given by. NC ( lox, ylex, y ) / lo, x, y X x y where l o, l e represents the original watermark and the extracted watermark inormation., (7) Original video rame TABLE II. PSNR AND SSIM ANALSIS OF WATERMARKED COLOUR VIDEO FRAME Δ = 8 Δ = 16 Δ = 4 PSNR SSIM PSNR SSIM PSNR SSIM Video Video Video Video st level DWT o video rame nd level DWT o video rame Fig. 6. DWT decomposition o video1 rame The Peak Signal to Noise Ratio (PSNR) penalizes the visibility o noise in the video rames. Thus, two video rames that are exactly the same will produce an ininite PSNR value. PSNR is given by: 55 PSNR 1 log (5) 1 MSE The Structural Similarity Index Measurement (SSIM) is a measure that compares local pattern o pixel intensities that have been normalized or luminance and contrast. The higher SSIM is, the larger the similarity between the compared video rames. SSIM is given by: SSIM (, ( L(, ).( C(, ).( S(, w )) (6) TABLE III. NC AND BER ANALSIS OF EXTRACTED COLOUR LOGO Δ Video1 Video Video3 Video Extracted logo NC BER Extracted logo NC BER Extracted logo NC BER.... TABLE IV. NC AND BER ANALSIS OF EXTRACTED WATERMARK UNDER ROTATION ATTACK Δ 1 Degree 3 degree 5 degree 7 Degree 9 Degree 8 NC BER NC BER NC BER

5 Bit Error Rate (BER) Normalized Correlation (NC) Normalized Correlation (NC) Bit Error Rate (BER) 15 Online International Conerence on Green Engineering and Technologies (IC-GET) TABLE V. NC AND BER ANALSIS OF EXTRACTED WATERMARK UNDER FILTER Δ Filter 3x3 Filter 5x5 Filter 7x7 Filter 9x9 8 NC BER NC BER NC BER Scaling actor = 4. TABLE VI. NC AND BER ANALSIS OF EXTRACTED WATERMARK UNDER SCALING ATTACK Δ 8% 7% 6% 5% 4% 3% 8 NC BER NC BER NC BER.5 As the watermark strength scaling actor increases, both PSNR and SSIM start to decrease. For example when the watermark strength scaling actor Δ = 1 or dierent images the PSNR was in the range 45 db to 47 db, but when Δ = 4 the PSNR was in the range 4dB to 41 db. The robustness o the DCT and Hash multi watermarking algorithm was tested by applying the various attacks such as JPEG compression, image resize, image cropping, image rotation, image iltering, noise and synchronization attack Video Frame Filter [size] Fig. 8. BER analysis o extracted watermark logo under ilter attack Scaling actor = 4.95 Scaling actor = Video Frame Scaling [%] Fig. 9. NC analysis o extracted watermark logo under scaling attack Scaling actor = Video Frame Filter [size] Fig. 7. NC analysis o extracted watermark logo under ilter attack Video Frame Scaling [%] Fig. 1. BER analysis o extracted watermark under scaling attack

6 Bit Error Rate (BER) Normalized Correlation (NC) 15 Online International Conerence on Green Engineering and Technologies (IC-GET) Scaling actor = Video Frame Rotation [degree] Fig. 11. NC analysis o extracted watermark under rotation attack Scaling actor = Video Frame Rotation [degree] Fig. 1. BER analysis o extracted watermark under rotation attack V. CONCLUSION This paper proposed a novel digital video watermarking technique using a hybrid DWT-DCT unction. In this study, a colour logo is utilized as a watermark and colour video rames are utilized as a cover. Based on our experimental results analysis we have come to the conclusion that the proposed video water marking is highly eicient and is capable o withstanding almost all sorts o signal processing attacks. The distortion caused by watermarking is assessed by using peak signal to noise ratio (PSNR) and similarity structure index measure (SSIM) and robustness against dierent types o attacks have been assessed using StirMark. Thereore, the proposed method is a very good candidate or copyright protection or video iles. Reerences [1] Saeed AL-Mansoori and Alavi Kunhu, Multi-Watermarking Scheme or Copyright Protection and Content Authentication o DubaiSat-1 Satellite Imagery, SPIE o Optics and Photonics Conerence 13, Caliornia, USA, August 13. [] M.Kim, D.Li and S. Hong, a Robust and Invisible Digital Watermarking Algorithm based on Multiple Transorm Method or Image Contents, Proceedings o the World Congress on Engineering and Computer Science 13 Vol I, WCECS 13,San Francisco, USA, October 13. [3] M. Swanson, M. Kobayashi, A. Tewik, Multimedia data embedding and watermarking techniques, Proc. IEEE 86 (1998) [4] A. Al-Gindy, H. Al-Ahmad, R. Qahwaj, and A. Tawik, "A requency domain adaptive watermarking algorithm or still colour images," in International Conerence on Advances in Computational Tools or Engineering Applications, ACTEA '9., Beirut, Lebanon, 9, pp [5] D. Kundur and D. Hatzinakos, Digital Watermarking using Multiresolution Wavelet Decomposition, Proceedings, IEEE International Conerence Acoustic, Speech, Signal Processing, [6] Alavi Kunhu and Hussain Al-Ahmad, A New Multi Watermarking Algorithm Based on DWT and Hash Functions or Color Satellite Images, IEEE International Conerence on Electronics, Circuits, and Systems- ICECS13, Abu Dhabi, UAE, December 13. [7] Huang Daren, Liu Jiuen, Huang Jiwu and Liu Hongmei A DWT based image watermarking algorithm, ICME IEEE International Conerence on Multimedia and Expo, August 1,pp [8] W. Lie, G. Lin, C. Wu, and T. Wang, Robust Image Watermarking on DCT Domain, ISCAS, IEEE International Symposium on Circuits and Systems, Geneva, Switzerland, May, pp [9] Saeed AL-Mansoori and Alavi Kunhu, Robust Watermarking Technique based on DCT to Protect the Ownership o DubaiSat-1 Images against Attacks, IJCSNS International Journal o Computer Science and Network Security, VOL.1 No.6, June 1. [1] Alavi Kunhu and Hussain Al-Ahmad, A New Watermarking Algorithm or Color Satellite Images Using Color Logos and Hash Functions, 5th IEEE International Conerence on Computational Intelligence, Communication System and Networks - CICSN13, Madrid, Spain, June, 13. [11] Z. Wang, A. Bovic, H. Sheikh, and E. Simoncelli, "Image Quality Assessment: From Error Visibility to Structural Similarity," IEEE Transactions on Image Processing, 4, pp ACKNOWLEDGMENT The authors acknowledge all the reviewers and editor in charge or their valuable comments on improving this paper.