Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis

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Internatonal Journal of Wsdom Based Computng, Vol. 1 (2), August 2011 7 Dgtal Vdeo Watermarkng usng Dscrete Wavelet Transform and Prncpal Component Analyss Sanjana Snha, Prajnat Bardhan, Swarnal Pramanck, Ankul Jagatramka, Dpak K. Kole, Aruna Chakraborty. Department of Computer Scence & Engneerng St Thomas College of Engneerng and Technology Kolkata, Inda. {aruna.stcet@gmal.com, dpak.kole@gmal.com, sanjanasnha89@gmal.com} Abstract - Due to the extensve use of dgtal meda applcatons, multmeda securty and copyrght protecton has ganed tremendous mportance. Dgtal Watermarkng s a technology used for the copyrght protecton of dgtal applcatons. In ths paper, a comprehensve approach for watermarkng dgtal vdeo s ntroduced. We propose a hybrd dgtal vdeo watermarkng scheme based on Dscrete Wavelet Transform (DWT) and Prncpal Component Analyss (PCA). PCA helps n reducng correlaton among the wavelet coeffcents obtaned from wavelet decomposton of each vdeo frame thereby dspersng the watermark bts nto the uncorrelated coeffcents. The vdeo frames are frst decomposed usng DWT and the bnary watermark s embedded n the prncpal components of the low frequency wavelet coeffcents. The mperceptble hgh bt rate watermark embedded s robust aganst varous attacks that can be carred out on the watermarked vdeo, such as flterng, contrast adjustment, nose addton and geometrc attacks. Keywords:- Dgtal vdeo; bnary watermark; Dscrete Wavelet Transform; Prncpal Component Analyss. I. INTRODUCTION The popularty of dgtal vdeo based applcatons [1] s accompaned by the need for copyrght protecton to prevent llct copyng and dstrbuton of dgtal vdeo. Copyrght protecton nserts authentcaton data such as ownershp nformaton and logo n the dgtal meda wthout affectng ts perceptual qualty. In case of any dspute, authentcaton data s extracted from the meda and can be used as an authortatve proof to prove the ownershp. As a method of copyrght protecton, dgtal vdeo watermarkng [2, 3] has recently emerged as a sgnfcant feld of nterest and a very actve area of research. Watermarkng s the process that embeds data called a watermark or dgtal sgnature nto a multmeda object such that watermark can be detected or extracted later to make an asserton about the object. The object may be an mage or audo or vdeo. For the purpose of copyrght protecton dgtal watermarkng technques must meet the crtera of mperceptblty as well as robustness aganst all attacks [4-6] for removal of the watermark. Many dgtal watermarkng schemes have been proposed for stll mages and vdeos [7]. Most of them operate on uncompressed vdeos [8-10], whle others embed watermarks drectly nto compressed vdeos [8, 11]. The work on vdeo specfc watermarkng can be further found n [12-15]. Vdeo watermarkng ntroduces a number of ssues not present n mage watermarkng. Due to nherent redundancy between vdeo frames, vdeo sgnals are hghly susceptble to attacks such as frame averagng, frame droppng, frame swappng and statstcal analyss. Vdeo watermarkng approaches can be classfed nto two man categores based on the method of hdng watermark bts n the host vdeo. The two categores are: Spatal doman watermarkng where embeddng and detecton of watermark are performed by drectly manpulatng the pxel ntensty values of the vdeo frame. Transform doman [16-18] technques, on the other hand, alter spatal pxel values of the host vdeo accordng to a pre-determned transform and are more robust than spatal doman technques snce they dsperse the watermark n the spatal doman of the vdeo frame makng t dffcult to remove the watermark through malcous attacks lke croppng, scalng, rotatons and geometrcal attacks. The commonly used transform doman technques are Dscrete Fourer Transform (DFT), the Dscrete Cosne Transform (DCT), and the Dscrete Wavelet Transform (DWT). In ths paper, we propose an mperceptble and robust vdeo watermarkng algorthm based on Dscrete Wavelet Transform (DWT) [19-25] and Prncpal Component Analyss (PCA) [26-28]. DWT s more computatonally effcent than other transform methods lke DFT and DCT. Due to ts excellent spato-frequency localzaton propertes, the DWT s very sutable to dentfy areas n the host vdeo frame where a watermark can be embedded mperceptbly. It s known that even after the decomposton of the vdeo frame usng the wavelet transformaton there exst some amount of correlaton between the wavelet coeffcents. PCA s bascally used to hybrdze the algorthm as t has the nherent property of removng the correlaton amongst the data.e. the wavelet coeffcents and t helps n dstrbutng the watermark bts over the sub-band used for embeddng thus resultng n a more robust watermarkng scheme that s resstant to almost all possble attacks. The watermark s embedded nto the lumnance component of the extracted frames as t s less senstve to the human vsual system (HVS). The paper s organzed as follows. Secton II contans the watermarkng scheme. Secton III contans the expermental results and fnally Secton IV gves the concluson.

Internatonal Journal of Wsdom Based Computng, Vol. 1 (2), August 2011 8 II. WATERMARKING SCHEME The watermarkng algorthm bascally utlzes two mathematcal technques: DWT and PCA. The sgnfcance of usng these technques n watermarkng has been explaned frst. A. Dscrete Wavelet Transform The Dscrete Wavelet Transform (DWT) s used n a wde varety of sgnal processng applcatons. 2-D dscrete wavelet transform (DWT) decomposes an mage or a vdeo frame nto sub-mages, 3 detals and 1 approxmaton. The approxmaton sub-mage resembles the orgnal on 1/4 the scale of the orgnal. The 2-D DWT (Fg. 1) s an applcaton of the 1-D DWT n both the horzontal and the vertcal drectons. DWT separates the frequency band of an mage nto a lower resoluton approxmaton sub-band (LL) as well as horzontal (HL), vertcal (LH) and dagonal (HH) detal components. Embeddng the watermark n low frequences obtaned by wavelet decomposton ncreases the robustness wth respect to attacks that have low pass characterstcs lke flterng, lossy compresson and geometrc dstortons whle makng the scheme more senstve to contrast adjustment, gamma correcton, and hstogram equalzaton. Snce the HVS s less senstve to hgh frequences, embeddng the watermark n hgh frequency sub-bands makes the watermark more mperceptble whle embeddng n low frequences makes t more robust aganst a varety of attacks. components and so on. The maxmum energy concentraton les n the frst prncpal component. The followng block dagram (Fg.2) shows the embeddng and extracton procedure of the watermark. In the proposed method the bnary watermark s embedded nto each of the vdeo frames by the decomposton of the frames nto DWT sub bands followed by the applcaton of block based PCA on the sub-blocks of the low frequency sub-band. The watermark s embedded nto the prncpal components of the sub-blocks. The extracted watermark s obtaned through a smlar procedure. Orgnal vdeo frame Watermark Apply DWT LL, HH Block based PCA Inverse PCA LL, HH IDWT Fgure 1. DWT subbands. B. Prncpal Component Analyss Prncpal component analyss (PCA) s a mathematcal procedure that uses an orthogonal transformaton to convert a set of observatons of possbly correlated varables nto a set of values of uncorrelated varables called prncpal components. The number of prncpal components s less than or equal to the number of orgnal varables. PCA s a method of dentfyng patterns n data, and expressng the data n such a way so as to hghlght ther smlartes and dfferences. Snce patterns n data can be hard to fnd n data of hgh dmenson, where the advantage of graphcal representaton s not avalable, PCA s a powerful tool for analyzng data. The other man advantage of PCA s that once these patterns n the data have been dentfed, the data can be compressed by reducng the number of dmensons, wthout much loss of nformaton. It plots the data nto a new coordnate system where the data wth maxmum covarance are plotted together and s known as the frst prncpal component. Smlarly, there are the second and thrd prncpal DWT Block based PCA Block based PCA of orgnal vdeo frame Fgure 2. Block Dagram of Watermarkng Watermarked Vdeo Extracted Watermark

Internatonal Journal of Wsdom Based Computng, Vol. 1 (2), August 2011 9 C. Algorthms for watermarkng usng DWT AND PCA Algorthm 1: a) Embeddng Procedure Step 1: Convert the n n bnary watermark logo nto a vector W = { w 1, w 2,, w n n } of 0 s and 1 s. Step 2: Dvde the vdeo (2N 2N) nto dstnct frames. Step 3: Convert each frame from RGB to YUV colour format. Step 4: Apply 1-level DWT to the lumnance (Y component) of each vdeo frame to obtan four sub-bands LL, LH, HL and HH of sze N x N. Step 5: Dvde the LL sub-band nto k non-overlappng sub-blocks each of dmenson n n (of the same sze as the watermark logo). Step 6: The watermark bts are embedded wth strength α nto each sub-block by frst obtanng the prncpal component scores by Algorthm 2. The embeddng s carred out as equaton 1. ' score = score + αw where score represents the prncpal component matrx of the th sub-block. Step 7: Apply nverse PCA on the modfed PCA components of the sub-blocks of the LL sub-band to obtan the modfed wavelet coeffcents. Step 8: Apply nverse DWT to obtan the watermarked lumnance component of the frame. Then convert the vdeo frame back to ts RGB components. b) Extracton Procedure Step 1: Dvde the watermarked (and possbly attacked) vdeo nto dstnct frames and convert them from RGB to YUV format. Step 2: Choose the lumnance (Y) component of a frame and apply the DWT to decompose the Y component nto the four sub-bands LL, HL, LH, and HH of sze N N. Step 3: Dvde the LL sub-band nto n n nonoverlappng sub-blocks. Step 4: Apply PCA to each block n the chosen subband LL by usng Algorthm 2. Step 5: From the LL sub-band, the watermark bts are extracted from the prncpal components of each sub-block as n equaton 2. ' ' ( score score ) W = (2) ' W s the watermark extracted from the th sub- where block. α (1) Algorthm 2: The LL sub-band coeffcents are transformed nto a new coordnate set by calculatng the prncpal components of each sub-block (sze n x n). Step 1: Each sub-block s converted nto a row vector wth n2 elements (=1,2 k ). Step 2: Compute the mean of the elements of vector D. Step 3: Compute D µ and standard devaton σ Z accordng to the followng equaton Z Here the same sze as that of ( D µ ) = (3) σ Z represents a centered, scaled verson of D. Step 4: Carry out prncpal component analyss on D, of (sze 1 x n 2 ) to obtan the prncpal component coeffcent matrx coeff (sze n 2 n 2 ). Step 5: Calculate vector score as Z score = Z coeff (4) where score represents the prncpal component scores of the th sub-block. III. EXPERIMENTAL RESULTS The proposed algorthm s appled to a sample vdeo sequence Lake.wmv usng a 32 32 watermark logo. The grayscale watermark s converted to bnary before embeddng. Fg. 3(a) and 3(b) show the orgnal and the watermarked vdeo frames respectvely. Fg. 4(a) s the embedded watermark and Fg. 4(b) s the extracted bnary watermark mage. The performance of the algorthm has been measured n terms of ts mperceptblty and robustness aganst the possble attacks lke nose addton, flterng, geometrc attacks etc. (a)

Internatonal Journal of Wsdom Based Computng, Vol. 1 (2), August 2011 10 (b) Fgure 3. (a) Orgnal Vdeo frame (b) Watermarked vdeo Fgure 5. Vdeo frame after addton of Gaussan nose (a) (b) Fgure 4. (a) Orgnal watermark (b) Extracted bnary watermark PSNR : The Peak-Sgnal-To-Nose Rato (PSNR) s used to devaton of the watermarked and attacked frames from the orgnal vdeo frames and s defned as: Fgure 6. Vdeo frame after addton of salt and pepper nose 2 PSNR = 10Log 10 (255 / MSE) (5) where MSE ( mean squared error ) between the orgnal and dstorted frames (sze m x n) s defned as: m n MSE = ( 1/ mn) [ I(, I (, ] (6) = 1 j= 1 where I and I are the pxel values at locaton (, of the orgnal and the dstorted frame respectvely. Hgher values of PSNR ndcate more mperceptblty of watermarkng. It s expressed n decbels (db). NC : The normalzed coeffcent (NC) gves a measure of the robustness of watermarkng and ts peak value s 1. NC = j j W (, W (, W (, j W (, where W and W represent the orgnal and extracted watermark respectvely. After extractng and refnng the watermark, a smlarty measurement of the extracted and the referenced watermarks s used for objectve judgment of the extracton fdelty. The followng mages represent stlls taken from the watermarked vdeo n after attacks have been carred on t. (7) Fgure 7. Vdeo frame after rotaton by 5 degrees Fgure 8. Vdeo frame after reszng Fgure 9. Vdeo frame after croppng

Internatonal Journal of Wsdom Based Computng, Vol. 1 (2), August 2011 11 Fgure 10. Vdeo frame after Gamma Correcton (varance 0.5) Fg. 5 and Fg. 6 show the watermarked vdeo frame after the addton of gaussan nose and salt and pepper nose respectvely. Fg. 7 shows the effect of carryng out vdeo frame rotaton by an angle of 5 degrees. Fg. 8 shows the watermarked vdeo frame after reszng frst by a factor of half followed by a factor to 2 to return t to ts orgnal sze. Fg. 9 shows the cropped vdeo frame. Fgures 10-14 show the effect of applyng gamma correcton (varance 0.5), contrast adjustment and automatc equalzaton. Fg. 14 and Fg. 15 show the resultant vdeo after applyng sharpenng flter and medan flter (3 3 box flter) respectvely. The followng table shows the value of the data collected from the watermarked vdeo after performng the varous attacks as shown prevously. TABLE I. RESULT ANALYSIS Attack PSNR NC Fgure 11. Vdeo frame after applyng Contrast Adjustment(factor 30). GAUSSIAN NOISE 31.1564 0.6861 SALT & PEPPER NOISE 24.4592 0.6548 CROPPING 28.3373 0.6801 ROTATION 28.8256 0.6510 RESIZING 41.4628 0.6068 Fgure 12. Vdeo frame after applyng automatc equalzaton. Fgure 13. Vdeo frame after applyng sharpenng flter (factor 50). MEDIAN FILTERING GAMMA CORRECTION SHARPENING FILTER CONTRAST ADJUSTMENT AUTOMATIC EQUALIZATION ATTACK 39.1676 0.5771 24.0749 0.5913 40.0710 0.5313 32.4420 0.5192 46.4597 0.6540 Fgure 14. Vdeo frame after medan flterng (3x3 box flter). Frame droppng: Frame droppng means droppng one or more frames randomly from the watermarked vdeo sequence. If we drop too many frames, the qualty of the watermarked vdeo wll decrease rapdly. In our experment, we only drop one frame randomly. Due to embeddng the same watermark nto each frame, t wll not affect the extracton of the watermark completely from attacked watermarked vdeo by frame droppng

Internatonal Journal of Wsdom Based Computng, Vol. 1 (2), August 2011 12 except that number of the extracted watermarks wll dffer. Frame swappng: Frame swappng means swtchng the order of frames randomly wthn a watermarked vdeo sequence. If we swap too many frames, t wll degrade the vdeo qualty. We have extracted all the watermarks from the vdeo after frame swappng. Frame averagng: Snce the frames are watermarked wth the same nformaton, the watermarked vdeos are not subject to the rsk of watermark estmaton by frame averagng snce the watermark sgnal gets amplfed on averagng. Thus from the expermental results t s qute evdent that the watermarkng algorthm s robust aganst all possble attacks. Other than ts computatonal complexty t has no dsadvantages. IV. CONCLUSION The algorthm mplemented usng DWT-PCA s robust and mperceptble n nature and embeddng the bnary watermark n the low LL sub band helps n ncreasng the robustness of the embeddng procedure wthout much degradaton n the vdeo qualty. 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