A Comparison between Digital Images Watermarking in Tow Different Color Spaces Using DWT2*

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1 A Comparson between Dgtal s ng n Tow Dfferent Color Spaces Usng DWT* Mehd Khall Natonal Academy of Scence of Armena Yerevan, Armena e-mal: khall.mehd@yahoo.com ABSTRACT A novel dgtal watermarkng for ownershp verfcaton and mage authentcaton applcatons usng dscrete wavelet transform (DWT) s proposed n ths paper. Most prevous proposed watermarkng algorthms embed sequences of random numbers as watermarks. Here bnary mages are taken as watermark for embeddng. In the proposed approach, the host mage s converted nto the YCbCr color space and then ts Y channel decomposed nto wavelet coeffcents. The selected approxmaton coeffcents are quantzed and then ther four least sgnfcant bts of the quantzed coeffcents are replaced by the watermark usng LSB nserton technque. At last, the watermarked mage s syntheszed from the changed and unchanged DWT coeffcents. The experments show that the proposed approach provdes extra mperceptblty and robustness aganst wavelet compresson compared to the tradtonal embeddng methods n RGB color space. Moreover, the proposed approach has no need of the orgnal mage to extract watermarks. Keywords Dgtal watermarkng, dscrete wavelet transform, YCbCr color space, LSB nserton technque, mperceptblty, wavelet compresson. 1. INTRODUCTION Wth the rapd growth of Internet technologes and wde avalablty of multmeda computng facltes, the enforcement of multmeda copyrght protecton becomes an mportant ssue [1]. Dgtal meda, e.g., mages, audo, and vdeo, are readly manpulated, reproduced, and dstrbuted over nformaton networks. These effcences lead to problems regardng copyrght protecton. As a result, creators and dstrbutors of dgtal data are hestant to provde access to ther dgtal ntellectual property. Techncal solutons for copyrght protecton of multmeda data are actvely beng pursued [, 3]. ng, whch allows for the mperceptbly embeddng nformaton n an orgnal multmeda data, has wdely emerged for copyrght protecton and ownershp dentfcaton. All watermarkng methods must satsfy three mportant requrements: perceptual nvsblty, robustness aganst varous mages processng, such as compresson and geometrc dstortons (for example croppng), and fnally ablty of watermarkng detecton wthout ambguty [4]. In ths paper dgtal mage watermarkng for ownershp verfcaton and mage authentcaton applcatons s presented, where watermark s a bnary mage that embeds n Y channel of YCbCr color space. Current technques descrbed n the lterature for the watermarkng of mages can be grouped nto two classes: spatal doman technques [5, 6] whch embed the data by drectly modfyng the pxel values of the orgnal mage, and transform doman methods [7,8] whch embed the data by modulatng the transform doman coeffcents. A varety of watermarkng technques has been proposed n recent years. One of the earler watermarkng technques, whch used wavelet transform, was based on the addng pseudo random codes to the large coeffcents at the hgh and mddle frequency bands of the dscrete wavelet transform [9]. The fundamental advantage of our wavelet-based technque les n the method used to embed the watermark n four bts of lowest sgnfcant bts of Y channel DWT approxmaton coeffcents of YCbCr color space of host mage usng LSB nserton technque. Wth ths proposed algorthm, we can obtan relatvely hgh payload (almost 0%). Expermental results show the effcency of proposed technques among other technques of dgtal mages watermarkng n wavelet transform doman. Ths results shows that watermarkng n YCbCr color space aganst compresson attacks s more robust than watermarkng n RGB color space, and has hgher transparency n same payload.. WAVELET TRANSFORM OF IMAGES The wavelet transform has been extensvely studed n the last two decades. Here, we ntroduce the necessary concepts of the DWT for the purposes of ths paper. The dscrete wavelet transform (DWT) s dentcal to a herarchcal subband system, where the subbands are logarthmcally spaced n frequency [10]. For an nput sequence of length n, DWT wll generate an output sequence of length n. The 1-D DWT can be completed by the drect pyramd algorthm developed by Mallat [11]. For a -D mage, a wavelet Ψ and a scalng functon Φ are chosen such that the scalng functon ΦLL (x, y) of low-low subband n a -D wavelet transform can be wrtten as ΦLL(x,y) Φ(x)Φ(y). Three other -dmensonal wavelets can also be obtaned by usng the wavelet assocated functon Ψ(x) as follows [9, 1, and 13]: ΨLH(x, y) Φ(x) Ψ(y); horzontal ΨHL(x, y) Ψ(x) Φ(y); vertcal ΨHH(x, y) Ψ(x) Ψ(y); dagonal Where H s a hghpass flter and L s a lowpass flter. The basc dea for the DWT of a -D mage s as follows: An mage s frstly decomposed nto four parts of hgh, mddle, and low frequency (.e., LL1, HL1, LH1, HH1) subbands by cascadng the mage horzontally and vertcally wth crtcally subsampled flter banks. The subbands labeled HL1, LH1, and HH1 represent the fnest-scaled wavelet coeffcents. To obtan the coarser-scaled wavelet coeffcents, the subband LL1 s further decomposed and crtcally subsampled. Ths

2 process s repeatedly a number of arbtrary tmes whch s determned by the applcaton at hand. Fg 1 shows an orgnal mage and ts DWT decomposton. In ths fgure, mage s decomposed nto three levels wth ten subbands. Each level has varous band-nformaton such as low-low, low-hgh, hgh-low, and hgh-hgh frequency bands [9]. Note that n Fg 1, the lowest frequency subband s at the top left, and the hghest frequency subband s at the bottom rght. Furthermore, from DWT coeffcents, the orgnal mage can be reconstructed. Ths reconstructon process s called the nverse DWT (IDWT). If I [m, n] represent an mage, the DWT and IDWT for I [m, n] can be smlarly defned by mplementng the DWT and IDWT on each dmenson m and n separately [9]. hde vsually recognzable patterns n mages. The proposed approach s based on the dscrete wavelet transform (DWT). In the proposed approach, the host mage s converted nto YCbCr channels; the Y channel s then decomposed nto wavelet coeffcents. Then, we embed watermark n the approxmaton coeffcents of DWT of the host mage by modfyng four least sgnfcant bts. The block dagram of the proposed watermarkng approach s shown n Fg. Fg1. A real case of DWT decomposton. (a) The orgnal mage. (b) Its DWT decomposton. 3. YCbCr COLOR SPACE YCbCr color space s used for color mages cryptography. In ths color space, the Y denotes the lumnance component. It means that Y shows the brghtness (luma). Also both of Cb and Cr represent the chromnance actors. It means that Cb s blue color mnus luma (B_Y) and Cr s red color mnus luma (R_Y) [13]. The dfference between YCbCr color space and RGB color space s that YCbCr color space represents color as brghtness and two color dfference sgnals, whle RGB represents color as red, green and blue. Equatons 1 and show transformatons between RGB color space and YCbCr color space [14]. Y R Cb G Cr 18 B (1) R G B () Y Cb 18 Cr PROPOSED WATERMARKING TECHNIQUE The current study task of dgtal watermarkng s to make watermarks nvsble to human eyes as well as robust to varous attacks. The proposed watermarkng approach can Fg. Block dagrams of the proposed watermarkng approach. (a) Embeddng procedure. (b) Extractng procedure embeddng method The algorthm for embeddng watermark n LL3 coeffcents of the host mage Y channel s descrbed as follows: Step 1: Convert RGB channels of a host mage W nto YCbCr channels usng the CCIR 601 standard. Step : Decompose the Y channel nto a three-level wavelet pyramd structure wth ten DWT subbands, F(H). The coarsest subband LL3 s taken as the target subband for embeddng watermarks. Step 3: Save the sgns of selecton coeffcents n a matrx sgn. Step 4: Quantze absolute values of selecton coeffcents. Step 5: Embed watermark W1. For robustness, mperceptblty, and securty, the watermark W s embedded n four least sgnfcant bts that have smallest quantzaton error. Step 6: Effect matrx sgn nto the embedded coeffcents. Step 7: Reconvert YCbCr channels of a changed host mage nto RGB channels. Step 8: A watermarked mage W' s then generated by nverse DWT wth all changed and unchanged DWT coeffcents. Step 9: Save ndexes of changed selecton coeffcents, and ndex of the embedded subband as the authentcated key. 4.. extractng method The embedded watermark can be extracted usng the stored authentcated key after wavelet decomposton of the

3 watermarked mage. The extractng process s descrbed as follows: Step 1: The RGB channels of the watermarked mage are converted nto YCbCr channels. Step : Decompose the Y channel nto ten DWT subbands. Step 3: Re-fetch the stored authentcated key. Step 4: Quantze absolute values of LL3 subband. Step 5: Extract four least sgnfcant bts of re-fetched key. The proposed watermarkng approach yelds satsfactory results n watermark mperceptblty and robustness. The PSNRs of the watermarked mages produced by the proposed approach are all greater than 37.5 dbs, NCs between orgnal watermark mages and extracted watermark mages are all equal 1, and correlatons between host mages and watermarked mages are all greater than 0.999, whch are perceptually mperceptble as shown n Fg EXPERIMENTAL RESULTS The proposed perceptual watermarkng framework was mplemented for evaluatng both propertes of mperceptblty and robustness n a hgh payload. Three mages: Lena, Peppers and Arm, shown n Fg 3(a-c) were taken as the host mages to embed a bnary watermark mage, shown n Fg 3(d). For the entre test results n ths paper, MATLAB R007a software s used. Also for computng the wavelet transforms, 9-7 borthogonal splne (Bsplne) wavelet flter are used. Cause of use of B-splne functon wavelet s that, B-splne functons, do not have compact support, but are orthogonal and have better smoothness propertes than other wavelet functons [15]. After watermark embeddng, we calculate the percentage of the payload as follows: % Payload W W 100 (3) Fg3. The host mages for watermarkng. (a-c) Lena, Peppers, and Arm. (d) mage In our scheme, we can obtan a payload, equal to %0. We also measure the smlarty of orgnal host mage and watermarked mages by the standard correlaton coeffcent (Corr) as [9]: ( x x )( y y ) ( x x ) ( y x ) (4) Correlato Moreover, the peak sgnal-to-nose rato (PSNR) was used to evaluate the qualty of the watermarked mage. The PSNR s defned as [9, 16]: 55 PSNR 10 log10 ( db) (5) MSE Where mean-square error (MSE) s defned as: 1 m n ( mn 1 1 h, and { } MSE h, h, ) (6) Where{ } h, are the gray levels of pxels n the host and watermarked mages, respectvely. The larger PSNR s, the better the mage qualty s. In general, a watermarked mage s acceptable by human percepton f ts PSNR s greater than 30 dbs. In other words, the correlaton s used for evaluatng the robustness of watermarkng technque and the PSNR s used for evaluatng the transparency of watermarkng technque [9]. We also used the normalzed correlaton (NC) coeffcent to measure the smlarty between orgnal watermarks W and the extracted watermarks W' that s defned as [17]: Fg4. The watermarked mages by the proposed approach Table 1 shows the extractng results and the watermarked mages usng the proposed method wthout any attacks. As t s vsble the watermarked results are excellent. Table 1. Obtaned results of watermark extractng PSNR Corr NC Error (db) Bts Lena Peppers Arm Robustness Examnatons After able to acheve the desred fdelty, watermarks robustness and ther watermarked mages detectablty evaluate under compresson and croppng attacks. w * w, NC w (7) Robustness to Compresson Attacks We here examne the watermark robustness wth wavelet compresson. We compress the watermarked mages wth dfferent compresson thresholds usng wavelet compresson.

4 Then, we extract the watermark from the compressed watermarked mages. The compresson results are llustrated n Table. From the table, we can fnd that proposed method yelds satsfactory mperceptble watermarked mages. All PSNRs are greater than 37 db, and all NC are greater than 0.83 under dfferent compresson thresholds of equal or less than 6. Table. Obtaned results of wavelet compresson attacks wth dfferent compresson thresholds Threshold 1.0 PSNR (db) NC Error Bts Threshold 3.0 PSNR (db) NC Error Bts Threshold 6.0 PSNR (db) NC Error Bts Furthermore, computng complcaton n YCbCr color space s greater than n RGB color space, too. Table 3. Obtaned results of croppng attacks Area 1 NC Error Bts Area NC Error Bts Table 4. Obtaned results of watermark extractng n RGB color space PSNR (db) Corr NC Error Bts Lena Peppers Robustness to Croppng Attacks In ths examnaton, we crop two dfferent areas of the watermarked mages and then, from the cropped mages, we extract the watermark mage. The results of the extracted watermarks are shown n Table 3. In ths table the cropped areas of watermarked maged and ther extracted watermarks are shown, too. As t s obvous, NCs are stll greater than WATERMARKING PROCESS IN RGB COLOR SPACE To consderaton of proposed technque effcency, we here perform watermarkng process n RGB color space by the same method. Then we compare the obtaned results of watermark extractng and robustness examnatons shown n tables 4, 5, 6, wth the prevous obtaned results. From the table 4, t can shown that transparency of watermarkng technque n YCbCr color space s better than n RGB color space, because of ts PSNRs. Also tables 5 and 6 show that, robustness to compresson attacks, n YCbCr color space s obvously greater than n RGB color space. In spte of these advantages, robustness to croppng attacks, n YCbCr color space s less than n RGB color space. Arm CONCLUSION We have proposed a watermarkng framework for embeddng vsually recognzable bnary watermark n color mages, whch can resst mage-processng attacks, especally the wavelet compresson attacks. In most DWT-based watermarkng frameworks, watermarks are often n the form of random-number sequences or gray-level mages. In ths paper, we proposed an mage accredtaton technque by embeddng bnary mage watermark nto color mages. In the proposed approach, a host mage was converted nto YCbCr color space usng the CCIR 601 standard, and then, the Y channel was decomposed nto wavelet coeffcents. Then, the watermark was embedded nto the four least sgnfcant bts of host coeffcents n the approxmaton coeffcents subband, usng LSB nserton technque. The expermental results show that the proposed method provdes extra mperceptblty and robustness of watermarkng aganst wavelet compresson attacks compared to the tradtonal methods n RGB color space. Moreover, the proposed approach has no need of the orgnal host mage to extract watermarks.

5 Table 5. Obtaned results of wavelet compresson attacks wth dfferent compresson thresholds n RGB color space Threshold 1.0 PSNR (db) NC Error Bts Threshold 3.0 PSNR (db) NC Error Bts Threshold 6.0 PSNR (db) NC Error Bts Table 6. Obtaned results of croppng attacks n RGB color space Area 1 NC Error Bts Area art overvew, IEEE Sgnal Processng Magazne, 17(9), pp. 0-46, 000. [3] P. Samulelson, Legally speakng, Dgtal meda and the law, Commune, ACM, 34(10), pp. 3-8, [4] V.V. Hernández Guzmán, M. N.Myatake, H.M. Pérez Meana, Analyss of a Wavelet-based ng Algorthm, IEEE, Proceedngs of the 14th Internatonal Conference on Electroncs, Communcatons and Computers (CONIELECOMP 04), 004. [5] R. G. van Schyndel, A. Z. Trkel, and C. F. Osborne, A dgtal watermark, In Proc. Int. Conference n Processng, vol., pp , [6] A. G. Bors and I. Ptas, watermarkng usng DCT doman constrants, In Proc, IEEE Int, Conference on Processng, vol. 3, pp , [7] J. Ohnsh and K. Matsu Embeddng a seal nto a pcture under orthogonal wavelet transform, In Proc, Int. Conference on Multmeda Computng and Systems, pp , June [8] Reza Safabakhsh, Shva Zabol and Arash Tabbazar, Dgtal ng on Stll s Usng Wavelet Transform, In IEEE Conf, Codng and Computng (ITCC 04), August 004. [9] X.G. Xa, C. G. Boncelet and G. R. Arce, Wavelet transform based watermark for dgtal mages, Optcs Express, pp , Dec [10] Mng-Shng Hseh, Wavelet-based ng and Compresson, Ph-D Thess, Insttute of Computer Scence and Informaton Engneerng Natonal Central Unversty, Tawan, Dec [11] S. Mallat, Multfrequency channel decomposton of mages and wavelets models, IEEE Trans. Acoustcs Speech and Sgnal Processng, vol. 37, no. 1, pp , Dec [1] Shh-Chung B. Lo, Hua L and Matthew T. Freedman, Optmzaton of Wavelet Decomposton for Compresson and Feature Preservaton, IEEE Transactons on Medcal Imagng, Vol., NO. 9, pp , September 003. [13] Manesh Kokare, P. K. Bswas and B. N. Chatter Texture Retreval Usng New Rotated Complex Wavelet Flters, IEEE Transactons on Systems, Vol. 35, No. 6, pp , December 005. [14] Douglas Cha Abdesselam Bouzerdoum, A Bayesan Approach to Skn Classfcaton n YCbCr Color Space. [15] Ingnemar Cox, Jeffrey Bloom and Matthew Mller, Dgtal ng: Prncple & Practce, Morgan Kaufnann Publshers, 1st edton, 001. [16] Martn Zlomek, Vdeo ng, M.S. Thess, Faculty of Mathematcs and Physcs, Charles Unversty n Prague, Aprl 007. [17] Jong Jn Chane, Robust Technques for Hdng Data n s and Vdeo, Ph.D Thess, Santa Barbara, Unversty of Calforna, June 000 NC Error Bts REFERENCES [1] H.M. Wang, P. Su and C.C. J. Kuo, Wavelet-based dgtal mage watermarkng, Dgtal Processng, Optcs Express 49, Vol. 3, No. 1, 7 December [] G. C. Langelaar, I. Setyawan, and R. L. Lagendk, ng dgtal mage and vdeo data, a state of the