Adaptve dgtal watermarkng of mages usng Genetc Algorthm Bushra Skander, Muhammad Ishtaq, M. Arfan Jaffar, Muhammad Tarq, Anwar M. Mrza Department of Computer Scence, Natonal Unversty of Computer and Emergng Scences, A. K. Broh Road, H-/4, Islamabad, Pakstan. {bushra.skander, m.shtaq, arfan.jaffar, m.tarq, anwar.m.mrza}@nu.edu.pk Abstract- Ths paper presents a new method for adaptve watermark strength optmzaton n Dscrete Cosne Transform (DCT) doman. Watermarkng s a method to embed secret nformaton n the host medum. Optmal strength selecton for watermark s the most crtcal aspect n the whole process and t had attracted many researchers n the recent past. In the proposed method watermark strength s ntellgently selected through Genetc Algorthm (GA). GA helps n perceptual shapng of the watermark such that t s less percevable to the human vsual system. Proposed method shows promsng results aganst dfferent attacks, such as lowpass flter, hgh-pass flter, medan flters, shftng and croppng the marked mage. Expermental results have shown better performance of the proposed method than the current approaches n practce. Index Terms: Dgtal watermarkng, dscrete cosne transform, perceptual shapng, genetc algorthm. I. INTRODUCTION Due to the rapd ncrease n the usage of nternet n the recent past, dgtal data such as audo, vdeo or mages are easly avalable to the publc. Hence protectng such nformaton has become more mportant. Due to ths avalablty many copyrght owners are concerned about protectng ther data or work from llegal replcaton. So t s necessary that some serous work must be done so that such llegal dstrbuton of data must be protected. Ths concern has drawn the attenton of the researchers towards the development of the dgtal mage protecton schemes. Out of many approaches proposed so far to protect the vsual data, dgtal watermarkng s the one that has possbly receved the most mportance. Dgtal watermarkng s embeddng any nformaton wthn the mage, vdeo [22], [23], [24], audo [25], [26], text or 3D [2], [22] models n order to make t secure from unauthorzed usage. A dgtal watermark can be descrbed as an nvsble or vsble recognton code that s embedded nto the data permanently. It means that unlke cryptography the watermarks can protect the content even after the decodng process. The watermark must be embedded n such a way that t does not affect the marked mage qualty and the sgnal embedded s hdden. The frst property s called robustness and the later one s called mperceptblty. Generally n dgtal watermarkng, the watermark s embedded wth the same strength nsde the whole mage. In ths process the local dstrbuton of the cover mage s not consdered. Such embeddng leads to some unwanted vsble objects n the watermarked mage. Mostly these are observed n smooth regons as they are more senstve to nose. The watermarkng strength should be decreased n order to decrease these deformatons. However, there s a possblty that the robustness of the mage s affected or s lost. Thus a sutable watermarkng strength should be selected for each pxel of the mage. Watermarkng s performed n spatal [27], [28], [29] as well as n frequency doman [5], [6], [7]. Recently researchers have been usng frequency doman watermarkng as t allows drect understandng of the content of the mage. When decdng about the strength and poston of the watermark to be embedded nto the mage, the human vsual system characterstcs can be taken nto account more easly. Cox et al., [5] and Pva et al., [3] have performed transformaton on the mage as a whole whle Boland et al., [4] have performed transformaton on block by block bass. Khan et al., [] optmzed the perceptual shapng of the watermark n the whole DCT doman. Hernandez et al., [5] Cox et al., [6] have used Watson s perceptual model [7] to shape the watermark n accordance wth the orgnal mage before the embeddng process. But they are usng an 8x8 block based DCT doman watermarkng. Hung et al., [8], [9] has used the Genetc algorthm to fnd the most favorable embeddng postons n the block-based DCT watermarkng scheme so that the marked mage qualty can be mproved. In ths paper we have used Genetc algorthm to adaptvely select the strength of watermark n the DCT doman. The md-band DCT coeffcents are selected to embed the watermark. In ths way better mperceptblty and robustness have been observed. The rest of the paper s organzed as follows. In secton 2 an ntroducton to genetc algorthm s descrbed. In secton 3 the proposed technque of watermark embeddng and detecton s descrbed. In secton 4 the mplementaton detals are dscussed. The results and dscusson are gven n secton 5. Fnally n secton 6 we conclude the remarks. II. GENETIC ALGORITHM Genetc algorthm (GA) [30] s an evolutonary global optmzaton technque. GA starts wth an ntal populaton of chromosomes.e. a randomly selected set of 978--4244-5943-8/0/$26.00 200 IEEE
chromosomes that encode a set of possble solutons. In GA, genes n a chromosome represent the varable of a problem and the chromosomes are evaluated accordng to a ftness crteron. Generally two genetc operators; crossover and mutaton are used for recombnaton. These genetc operators are used to alter the composton of the genes to create new chromosomes (offsprngs). Mutaton alters a small part of the chromosomes whereas crossover changes the genetc materal of the chromosomes. The selecton operator, the Darwnan survval of the fttest among the populaton, s an artfcal verson of natural selecton. Ths s the process of selectng the best chromosomes to create new populaton from one generaton to another. The chromosomes that have hgher ftness have the hgher probablty of beng selected for the next generaton. The GA s shown as follows [8-]. Let P(t) and C(t) be the parent and chld (offsprng) n generaton t. Procedure: GenetcAlgorthm Begn: t 0; Intalze P(t); Evaluate P(t); Whle (not meet termnaton crteron) do Recombne P(t) to create C(t); Evaluate C(t); Select P(t+) from P(t) and C(t); t t + ; End; End; III. PROPOSED METHOD Dgtal watermarkng s the process of embeddng some nformaton nto the dgtal mage or meda by makng some small modfcatons. But these small modfcatons should not affect the mage s vsblty to a large extent. These small modfcatons should also be able to survve some ntentonal or unntentonal attacks. Snce we are focusng on only dgtal mage watermarkng, therefore the mage should be able to survve the common forgery attacks. Even f the attacker s able to remove the watermark from the host mage, the usablty of the mage s lost, hence the watermark must survve n the host medum tll the usablty of the medum s ntact. Cox et al. [5] proposed the usage of a pseudo random sequence of real numbers as the watermark so that nvsblty can be acheved. These sequences should be easly retrevable and should be numerous. Therefore followng hs dea our watermark s also a pseudo-random sequence of real numbers. Watermark should be able to resst the ntentonal attacks. Also the watermark could be easly detectable or extractable from the corrupted and nosy mage. There are two types of watermarkng technques [2] blnd [6] and non-blnd [5]. The frst does not requre the orgnal mage at the tme of detecton whle the later requres the orgnal mage n the extracton process. We have followed the frst technque. A. Dgtal watermark embeddng process In embeddng phase, a pseudo random sequence as the watermark W s nserted nto the orgnal mage I of sze M x N. The embeddng algorthm s as followng: Step : The DCT transformed mage D of I can be obtaned as M 2 (, ) ( ) ( ) N D u v = a u a v x I ( m. n)... MN m= 0 n= 0 (2m + ) uπ (2n + ) vπ cos cos () 2 2 M N / M for u = 0 where a ( u ) = 2 / M for u =,2,..., M / N for v = 0 and a ( v ) = 2 / N for v =, 2,..., N Step 2: After obtanng D, a zgzag scannng s done n order to select the coeffcents for embeddng [6] Zgzag scannng order s gven n fg. 4. Snce the perturbaton n low frequency components as compared to hgh frequency components s generally more percevable to the human eyes therefore ths task s equvalent to sortng accordng to the mportance. Step 3: The ntalzaton of GA s performed. For each chromosome of the GA followng steps are performed. a: The frst L coeffcents are left ntact and the watermark s beng embedded nto the next L+M coeffcents. Suppose the frst L+M DCT coeffcents are: C = { c, c 2,, c L, c L +,, c L + M } (2) And the pseudo-random watermark s gven by W = { w, w2,, w } (3) M The new coeffcents obtaned after embeddng are ~ c L+ = cl+ + α cl+ w (4) where s the watermarkng strength and has values from L to M. b: These newly obtaned coeffcents are renserted nto the zgzag scannng. c: Then by takng the nverse of the modfed DCT coeffcents the watermark mage n the spatal doman s obtaned. d: Calculate the ftness of each chromosome so that the GA operators.e. crossover and mutaton can be appled. Step 4: Repeat steps a-d untl the termnaton crtera s acheved. The block dagram of embeddng process and the GA smulaton are shown n Fgure and Fgure 2 respectvely as below B. Dgtal watermark detecton process Durng the detecton process, Pva et al., [6] used the reverse process for a gven corrupted mage. The detecton algorthm s as followng:
Step : Frst the DCT coeffcent matrx of sze M x N s computed. Step 2: Then t s reordered by the zgzag scan. Step 3: Watermark coeffcents from L+ to L+M are selected to form a matrx as follows. ~ C = c,..., ~ L+ c L+ M (5) Step 4: The correlaton of and any matrx s calculated as: Z = W C = M M M = w c L + α (6) Step 5: Ths correlaton Z s then compared to a predefned threshold to determne whether the watermark exsts or not. The block dagram of watermark detecton s shown n Fgure 3. Fgure 2: Chromosome encodng The ftness s computed for each chromosome and then the chromosomes wth hgher ftness are selected for matng usng the crossover and mutaton operators, so that a new populaton of chromosomes s created for the next generaton. Intally, for a populaton sze of 0 chromosomes and 50 generaton, the GA smulaton takes 0 mnute on a Pentum IV- 2.0 GHz machne. Orgnal mage of sze N x N Intalze GA Fnd the DCT coeffcents Apply DCT on mage Evaluate each ndvdual (chromosome) Apply zgzag scan DCT coeffcents are reordered Recombnaton (Crossover/Mutaton) Key Pck selected frequency coeffcents GA Smulaton Evaluate the offsprngs created Watermark Embeddng process Watermarkng strength Selecton of parent and off sprngs Obtan marked DCT coeffcents Apply nverse zgzag scan No Meet termnaton crtera? Watermark mage obtaned Apply nverse DCT Yes Fnd watermarked mage Fgure : Watermark embeddng process IV. IMPLEMENTATION DETAILS To represent a possble soluton usng GA, the chromosome structure, ftness functon, sutable crossover rate, and mutaton rate, populaton sze and maxmum generaton sze must be defned. For the manpulaton of mages ncludng the DCT of the orgnal mage and the selecton of the DCT coeffcents Matlab [20] has been used. The selected coeffcent array and the watermarkng strength are used to embed the watermark nto the mage. The selected DCT coeffcents and the watermarkng strength together make a sngle chromosome as shown n fgure below. Fgure 3: GA Smulaton Fgure 4: Zgzag scan
Table : Orgnal and marked mages of sze 52 x 52 Orgnal mage of sze N x N Name Orgnal mage Watermarked mage Apply DCT on mage Fnd the DCT coeffcents Apply zgzag scan DCT coeffcents are reordered Pck selected frequency coeffcents Dfferent Watermarks Watermarkng strength Compute Correlaton Watermark found? Fgure 4: Watermark Detecton The chromosome wth the hghest ftness of the last generaton s then coped and t s used for watermark embeddng n the Matlab envronment. Mean Squared Error (MSE) and Peak Sgnal to Nose Rato () as gven by (7) and (8) are used to check the perceptual mperceptblty of the watermarked mage. MSE = MN M N [ I (m, n) I (m, n)] ' 2 (7) m = 0 n =0 ( I MAX ) 2 = 0 log0 MSE ¹ (8) Where I s the orgnal mage and I' s the watermarked mage. IMAX s the maxmum possble value of the mage I, for an 8-bt per pxel representaton IMAX s 255. Table 2: Performance by varyng generaton sze, best values are n bold face. Standard mages V. EXPERIMENTAL RESULTS AND DISCUSSION A. Watermark embeddng: We have frstly used the standard mage as the cover mage n order to check the robustness of our proposed watermarkng method. The marked mages are shown n table. The mage s marked usng L = 25000 and M = 6000. The watermarkng strength for each DCT coeffcent s optmzed usng GA. The optmzed strength s n the nterval [0, ]. Followng seres of experments were performed on the standard watermarkng mages to fnd the optmal value of the GA parameters for adaptve watermark strength selecton. Results for 4 mages.e.,, and mages are provded n the paper. Experment seres : Effect of Generaton sze By keepng all the parameters of GA constant and only varyng the no. of generatons from 50 to 250 wth an nterval of 50, the mean, MSE and SSIM readngs over 00 runs of each experment are gven as follows: Performance MSE SSIM MSE SSIM MSE SSIM MSE SSIM Generatons Evolved 50 200 250 45.2387 45.2443 45.2457.9464.9439.9434 0.987 0.9872 0.9872 43.909 43.8759 43.936 2.6424 2.6639 2.6298 0.9856 0.9856 0.9857 39.575 39.5773 39.634 7.708 7.673 7.0747 0.9826 0.9825 0.9828 45.5906 45.5996 45.672.7949.792.7839 0.989 0.989 0.9892 Here the value of populaton sze was kept 30 chromosomes, the crossover rate was chosen as 70% and the mutaton rate was selected as 30%. From table 2 we can see that for and mage the best s obtaned for 50 generatons and for and mage t s obtaned at 200 generatons. So n next experment.e. varyng the populaton sze we wll use the respectve best generatons of the mages. Experment seres 2: Effect of Populaton sze
By only varyng the populaton sze from 0 to 30 wth an nterval of 0 whle keepng the rest of the parameters of GA constant, the mean, MSE and SSIM readngs over 00 runs of each experment are gven as follows: Standard mages Table 3: Performance by varyng populaton sze Performance Populaton sze 0 20 30 45.2267 45.2920 45.2457 MSE.958.9230.9434 SSIM 0.987 0.9873 0.9872 43.8882 43.938 43.936 MSE 2.6563 2.6262 2.6298 SSIM 0.9856 0.9857 0.9857 39.5834 39.5708 39.634 MSE 7.572 7.780 7.0747 SSIM 0.9826 0.9827 0.9828 45.6070 45.6058 45.672 MSE.788.7886.7839 SSIM 0.989 0.989 0.9892 Here the value of maxmum no. of generaton was kept 50 for and and 200 for both and mages. The best, MSE and SSIM were obtaned for these generaton no. on these mages n the prevous experment. The crossover rate was kept constant as 70% and mutaton rate as 30% for the standard mages. From table 5 t can be seen that for both and mage the best s obtaned for populaton sze of 20 chromosomes and for both and mage the best s obtaned for populaton sze of 30 chromosomes. So now we wll use these values of populaton szes of respectve mages n the next experment of varyng the crossover rate. Experment seres 3: Effect of Crossover rate Now by varyng the crossover rate and keepng the rest of the GA parameters constant we get the followng results. Table 4: Performance by varyng crossover rate Standard mages Performance Crossover rate 0.5 0.6 0.7 45.283 45.28 45.297 MSE.927.927.92 SSIM 0.987 0.987 0.987 43.905 43.902 43.96 MSE 2.646 2.648 2.640 SSIM 0.986 0.986 0.986 39.567 39.595 39.563 MSE 7.86 7.39 7.9 SSIM 0.983 0.983 0.983 45.664 45.603 45.626 MSE.765.790.78 SSIM 0.990 0.989 0.989 Standard mages Performance Crossover rate 0.8 0.9 45.252 45.264 45.277 MSE.940.935.929 SSIM 0.987 0.987 0.987 43.907 43.903 43.90 MSE 2.646 2.648 2.690 SSIM 0.986 0.986 0.986 39.559 39.68 39.572 MSE 7.98 7.02 7.78 SSIM 0.983 0.983 0.983 45.575 45.66 45.622 MSE.802.7842.782 SSIM 0.989 0.990 0.990 The generaton sze and populaton sze was selected from the best s of experment and 2. And mutaton rate was kept 0.3. From table 8 we can compare the mean, MSE and SSIM; best crossover rate for each mage s gven n boldface. Experment seres 4: Effect of Mutaton rate Followng table s obtaned by varyng the mutaton rate and keepng the remanng GA parameters constant. Table 5: Performance by varyng mutaton rate Standard mages Performance Mutaton rate 0.3 0.4 0.5 45.2920 45.236 45.2684 MSE.9230.9498.9332 SSIM 0.9873 0.987 0.9872 45.938 43.898 43.9277 MSE 2.6262 2.6542 2.6322 SSIM 0.9857 0.9856 0.9857 39.634 39.6354 39.6238 MSE 7.0747 7.072 7.09 SSIM 0.9828 0.9827 0.9829 45.672 45.6369 45.625 MSE.7839.7759.782 SSIM 0.9892 0.9892 0.9892 The values of the GA parameters as obtaned from experment, 2 and 3 were chosen for the standard mages. The best results were observed at mutaton rate of 0.3 for and and 0.4 for and mages. We have compared our results wth Khan et al., []. The comparson table s shown below: Table 6: Comparson of our technque wth other technques Standard mages 45.292 43.938 39.6354 45.6369 Proposed method MSE.923 2.6262 7.072.7759 MSS 0.0822 0.0828 0.0826 0.0834 SSIM 0.9873 0.9857 0.9827 0.9892 44.45 40.94 36.28 39.59 A. Khan et al. [] MSE 0.6287.53 3.884.84 MSS 0.047 0.047 0.047 0.048 4.525 39.69 36.066 37.88 WPM MSE 4.5902 7.873 6.085 0.59 SSIM 0.9809 0.9809 0.98 0.9809 A. Khan et al. [2] GPM 38.492 36.5404 34.408 36.504 MSE 9.357 4.7246 23.5636 5.777 SSIM 0.98 0.9809 0.98 0.9809
Here MSS s the mean squared strength of the watermark. It can be calculated as follows: MSS = G G = α 2 (9) Were G s the number of coeffcents selected for watermark embeddng and s the strength of watermark for each th coeffcent. In our case hgh strength watermark was used for embeddng then Khan et al. [], but stll our, MSE and SSIM shows better performance because n our case the watermark s dstrbuted n the less percevable regons of the mages. B. GA Parameters: The values of GA parameters are gven n Table 5 as below. Table 7: GA Parameters Selecton Rank based Max. Generatons 50 (for and ) 200 (for and ) Populaton sze 20 (for and ) 30 (for and ) Crossover rate 70% Mutaton rate 30% (for and ) 40% (for and ) Ftness measure The value of maxmum generaton no., populaton sze, crossover rate and mutaton rate are obtaned by the above experments performed. C. Watermark detecton: The values of L = 25000 and M = 6000 has been used for the standard mages durng the detecton process. Then the marked mage s checked for correlaton wth randomly generated 000 watermarks. The hghest correlaton s consdered to be representng the orgnal watermark used n the embeddng process. The detected watermark for the standard mage s shown below: Fgure 5 and Table 8, 9, 0 confrm the robustness of our proposed watermarkng technque wth dfferent attacks. Fgure 6: Detector response wth 3x3 medan attack on mage Dfferent attacks were carred out on the watermarked mages and t survved all the attacks wth the excepton of croppng 90% of the mage, n ths case the usablty of the mage s also lost due to croppng. Hence, n our case watermark survved all the attacks tll the usablty of the watermarked mages s ntact. Table 8: Comparson of the system under dfferent attacks for mage and results comparson wth [] Attack MSE MSE Proposed [] Proposed [] 2x2 86.5264 86.33 28.76 2.6 Medan 3x3 28.46 27.87 33.64 26.52 flter 4x4 02.8666 02.45 28.0 20.84 5x5 69.3397 68.73 29.72 22.57 2x2 8.6277 8.47 29.0 2.86 Low-pass 3x3 49.5376 49.37 3.8 24.0 flter 4x4 2.663 2.37 27.6 20.4 5x5 5.054 4.65 27.52 20.30 Hgh-pass flter 3x3 42.5388 42.34 3.84 24.8 Table 9: Performance on cropped mages Image Croppng MSE SSIM x 28.7240 87.2329 0.9992 50x50.5825 456.845 0.6550 00x00 9.684 7874.7879 0.3754 50x50 7.9487 0428.459 0.725 70x70 7.6923 062.4978 0.33 Fgure 5: Detecton of watermark for mage D. Survval aganst attacks:
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