Robust Watermarking for Text Images Based on Arnold Scrambling and DWT-DCT

Transcription

1 Internatonal Conference on Mechatroncs Electronc Industral and Control Engneerng (MEIC 015) Robust Watermarkng for Text Images Based on Arnold Scramblng and DWT-DCT Fan Wu College of Informaton Scence and Technology Hanan Unversty Hakou Chna Mengxng Huang College of Informaton Scence and Technology Hanan Unversty Hakou Chna Jngbng L* College of Informaton Scence and Technology Hanan Unversty Hakou Chna Abstract Wth the popularzaton of Internet and the development at full speed of the mult-meda technology the copyrght protecton of dgtal works has already become the hot ssue at present. The paper proposes lnd watermarkng algorthm for text mages authentcaton and protecton based on DWT-DCT. Frstly the text mage s decomposed nto a low frequency horzontal vertcal and dagonal four components though DWT transformaton then the low frequency component s made the whole DCT transform to get rd of coeffcent correlaton n order to obtan the vsual feature vectors. Based on the studes of the document dgtal watermarkng methods and technques ths dssertaton presents that the problems of exsted documents watermarkng algorthms can be solved by Arnold Scramblng and DCT technque. The expermental results show that the scheme has strong robustness aganst common attacks and geometrc attacks. Keywords-Arnold scramblng; Dgtal Watermarkng; DWT; DCT; Zero-watermarkng; Text mage. I. INTRODUCTION Wth the rapd development of computer scence and technology and multmeda communcaton technology dgtal meda s becomng more and more unversal. Dgtal watermarkng s an mportant method for protectng dgtal meda copyrght. Most work focuses on audo vdeo grayscale and color mages. However bnary mages are very useful for securty records nsurance nformaton fnancal document fax mages case hstory contract e-busness e- Government etc. Therefore t may be very useful to embed and extract watermarkng n bnary mages. Currently the dgtal watermarkng technque s appled n the transform doman more popular than appled n the spatal doman []. DCT s wdely used among the transform doman and DWT based technques have also been popular appled because of ts excellent spatal localzaton and multresoluton propertes. In ths paper we have proposed a DWT -DCT based blnd watermarkng algorthm for copyrght protecton. The combnaton of the two transforms mproves the watermarkng performance compared to the DWT or DCT only watermarkng approach. In addton the watermarkng s scrambled and embedded n a spread spectrum pattern so as to enhance the securty and robustness further. Experment evaluaton results show that the proposed algorthm has strong ablty n resstng common attacks and geometrc attacks. II. THE FUNDAMENTAL THEORY A. The Dscrete Wavelet Transform The wavelet transform proposed by S. Mallat n 1988 frstly s a new sgnal analyss theory and a tme-frequency method. The basc dea s to decompose the sgnal f t based on wavelet functon t. Wf ( a b) f ( t) a b( t) dt R t Where wavelet functon s a set of functons whch are obtaned by translatng and stretchng of the same base functon t. 1 ( t ) a (( t b ) a ) a b R a 0 a b Where s the basc wavelet a and b are the dlaton factor and the translaton factor respectvely. The decomposng equaton of Mallat algorthm s defned as follows: c 1 k c nh k R nk nz d c g 1 k n nk nz k z The reconstructon equaton of the Mallat algorthm s gven by: c k c 1 nhkn d k z 1 ng k n nz By the one-layer wavelet decomposton of the orgnal mage four subband mages can be acqured. Where LL1 s the approxmated subband mage wth low frequency nz 015. The authors - Publshed by Atlants Press 568

2 characterstcs that are robust to attacks. The others (LH1 HL1 and HH1) wth hgh frequency characterstcs are easly affected by attacks. Therefore embeddng the watermarkng nto the low frequency subgraph can provde better robustness. B. The Dscrete Cosne Transform DCT transform s compatble wth nternatonal data compresson standard (JPEG MPEG) and s wdely used. It s well known for the best balance between operaton speed and hgh precson of extractng the feature vector [3]. The M N text mage s DCT transform s defned by: M 1 N 1 (x 1) u (y 1) v F( u v) c( u) c( v) f ( x y)cos cos M N x0 y0 u M 1; v N 1 1 M u 0 1 N v 0 c( u) c( v) M u 1... M 1 N v 1... N 1 Where x y s sampled value n the spatal doman samplng; u v s the frequency doman samplng. Usually dgtal mage s expressed by pxels square namely M=N. C. Arnold scramblng Transform (AT) Scramblng transformaton as a means of encrypted technology s appled n the pretreatment stage of the watermarkng after scramblng transformaton one meanngful watermarkng wll become a meanngless chaotc mage. If you do not know the scramblng algorthm and keys an attacker even got the embedded watermark can't restore t. And thus plays a role of secondary encrypton. Addtonally after scramblng transformaton t wll upset the relatonshp between the space locatons of pxels and make t evenly dstrbuted n all space of the carrer mage. Ths wll mprove the robustness of the algorthm. Two-dmensonal Arnold scramblng transformaton s defned as follows: x ' 1 1 x mod N x y 01 N 1 y ' 1 y (7) Wheren x y s the pxel coordnates of the orgnal space: x' y' s the pxel coordnates after teratve computaton scramblng N s the sze of the rectangular mage also referred to as a step number. By the above formula the correspondng nverse transform formula can be obtaned: x 1 x ' N mod N x ' y ' 01 N 1 y 1 1 y ' N (8) It s easy to restore the orgnal ntal state accordng to the correspondng teratons. Arnold transformaton s cyclcal when terate to a step wll regan orgnal mage. So f you do not know cycle and teratons you wll not be able to restore the mage. Therefore cycle and teratons can exst as a prvate key. Meanwhle dfferent mage because the desred effect s dfferent teratons should also be changed accordng to your need. D. A method to obtan the feature vector of text mage Feature extracton means to obtan the feature vector whch s used to descrbe the mage content. In lterature the common characterstcs are usually the followng types: gray feature Shape and locaton [4] texture features [5] and semantc features. Frstly DWT s appled on the orgnal text mage to obtan the approxmated subband LL1. Then DCT of the whole LL1 s computed and the DCT coeffcent matrx s acqured. We choose 5 low-frequency DWT-DCT coeffcents (F(11) F(1) F(15)) for formaton of the feature vector shown n Table I. We fnd that the value of the low-frequent coeffcents may change after the mage has undergone an attack partcularly geometrc attacks. However the sgns of the coeffcents reman unchanged even wth strong geometrc attacks as also shown n Table I. Let 1 represents a postve or zero coeffcent and 0 represents a negatve coeffcent and then we can obtan the sgn sequence of low-frequency coeffcents as shown n the column Sequence of coeffcent sgns n Table I. After attacks the sgn sequence s unchanged and the normalzed cross-correlaton (NC) s equal to 1.0. Ths means that the sgns of the sequence can be regarded as the feature vector of the text mage. Furthermore t proves that the sequence of the DWT-DCT coeffcent sgns can reflect the man vsual characterstcs of text mages. T ABLE Ⅰ. CHANGE OF DWT-DCT LOW-FREQUENCY COEFFICIENTS WITH RESPECT TO DIFFERENT ATTACKS. C1 C C3 C4 C5 C6 C7 C8 C9 C10 C11 C1 C13 C14 Image processng PSNR F(11) F(1) F(13) F(14) F(15) F(16) F(17) F(18) F(19) F(110) Sequence of coeffcent sgns NC Orgnal mage Gaussan nose (4%) 13.0dB JPEG compresson (5%) 17.71dB Medan flter [3 3] 8.535dB Croppng(%) 5.439dB (fromy drecton) Rotaton (1.5 ) 5.598dB Scalng( 0.5) DCT transform coeffcent unt 1.0e

3 III. THE ALGORITHM Use a meanngful bnary mage as the watermarkng Represented by W F represents the orgnal text mage The W={ w() w() =01;1 M11 M} as dgtal watermarkng At the same tme we select a paragraph n an artcle as the orgnal text mage. It s descrbe as: F={ f() f() R;1 N11 N} where w (( )) and f ( ) denote the pxel gray values of the watermarkng and the orgnal text mage Let M1 = M = M N1 = N = N. A. The algorthm of the embedded watermarkng. Step1 the bnary watermarkng mage s scrambled by Arnold scramblng transform BW(). BW ( ) AT ( W (. )) (9) Step L-level decomposton of the wavelet transform to the orgnal text mage and obtanng the approxmaton subgraph FA L. The orgnal text mage after L level wavelet decomposton Can get more detals sub-graph coeffcent FD k (k=13;=13 L) and an approxmaton sub-graph coeffcent FA L. Wavelet decomposton level L floor(log(n/m)) f L level wavelet decomposton seres s hgh the wavelet coeffcent resstance to gaussan JPEG compresson and conventonal attack ablty wll become strong but wavelet decomposton and the reconstructed tme correspondng lengthened. Here take L = 1. FA( ) DWT ( F( )) (10) Step3 Full fgure DCT transformaton on approxmaton subgraph FA L get text mage vsual feature vector V (). Frstly DCT of the whole approxmated subband LL1 FA L () s computed and the DCT coeffcent matrx FF() s acqured. Then Zg - Zag sort to FF(). Next the frequency sequence Y() from low to hgh frequency can be obtaned. Fnally the feature vector V() V { v( ) v( ) 0.1;1 J} s acheved as the sgns sequence of the low-frequency DWT-DCT coeffcents where the value of J can tune the robustness and capablty of the embedded watermarkng. FF( ) DCT ( FAL ( )) (11) Y ( ) Zg Zag( FF( )) (1) V ( ) Sgn( Y ( )) (13) Step4 Use HASH functon propertes and vsual feature vector Acqure the key sequence. Key( ) V ( ) BW ( ) (14) Key ( ) s by the mage vsual feature vector and the embed watermarkng BW ( ) generated by the HASH functon of cryptography. Key ( ) s used to extract the watermarkng Furthermore Key ( ) can be regarded as a secret key and regstered to the thrd part to preserve the ownershp of the orgnal text mage so as to acheve the purpose of the protecton of text mages. C. The algorthm of the extracted watermarkng. Step1 Get the approxmaton sub-graph of the beng tested mage by the wavelet transform. Let the beng tested mage for Test_F '( ) abbrevated as T_F '( ) L-level decomposton of the wavelet transform to the beng tested mage and obtanng the approxmaton subgraph T_FA L ' (). FA( ) DWT ( F( )) (15) Step Full fgure DCT transformaton on approxmaton subgraph T_FA L (). get text mage vsual feature vector T_V (). ' ' FF DCT FAL ( ) ( ( )) (16) Y ( ) Zg Zag( FF( )) (17) T _ V '( ) Sgn( Y '( )) (18) Step3 Extractng the watermarkng BW ' ( ). Accordng to the key whch generated n the embedded watermarkng and the vsual feature vector T_V '() of the beng tested mage use HASH functon propertes to extract the watermarkng BW ' ( ). Extractng watermarkng doesn't need orgnal mage so t can protect the orgnal mage better. BW '( ) Key( ) T _ V '( ) (19) Step4 Usng the Arnold scramblng nverse transform to restore the extracted watermarkng BW '( ) get the watermarkng of the beng tested mage W (). W ( ) IAT ( BW ( )) (0) D. Detecton algorthm of the watermarkng. Step1 By calculatng NC (Normalzed Cross-Correlaton) to determne whether there s the exstence of the watermarkng. The larger the value of NC s the more approxmaton between W '( ) and W ( ). Defned as: NC W W ' W (1) Where W ( ) s the orgnal watermarkng W '( ) s the extracted watermarkng. Step Evaluaton of the qualty of the text mage after Embed watermarkng by calculatng the peak sgnal-to-nose rato PSNR (db) we often use peak value sgnal-to-nose rato PSNR (db) to reflect the qualty of sgnal defned as: 570

4 PSNR I MN max I 10lg I' () where I() I'() denote the pxel gray values of the coordnates () n the orgnal mage and the watermarkng respectvely; M N represent the mage row and column numbers of pxels respectvely. IV. EXPERIMENTS To verfy the effectveness of our proposed algorthm we carred out the smulaton n Matlab010a platform. We choose a sgnfcant bnary mage as the orgnal watermarkng and select a paragraph n an artcle as the orgnal text mage. the orgnal watermarkng W= {w() w()=0 or 1; }. the orgnal text mage F={f () }. In the experment the parameter values: Arnold scramblng perod s 4 and the number of transform tmes are 8.e. T=4 n=8. It can be seen vsually from Fgure 1 that the qualty of the text mage embedded has hardly any change. The qualty of extracted watermarkng s of hgh-qualty wth no dfference wth the orgnal n normal case (no attackng on watermarkng). (c) Fgure 1. The watermarkng s scrambled by Arnold scramblng transform. The watermarked text mage wthout attacks the orgnal bnary watermarkng. (c) the scrambled watermarkng. In order to nvestgate ths approach of embeddng watermarkng robust performance I chose the followng verfcaton: A. Common attacks. 1) Addng Gaussan nose. In the watermarked text mage Gaussan nose s added by the mnose functon wth dfferent nose level. The text mage under the attack of Gaussan nose (10%) wth PSNR=13.0Db. At ths tme the watermarked text mage has been very vague as shown n Fg. 3. The watermarkng can obvously be extracted wth NC=1.0. As shown n Fg. 3. Table Ⅱ shows the NC values between the extracted and embedded watermarkng and the PSNR of the attacked watermarked mage. TABLEⅡ THE PSNR AND NC UNDER GAUSSIAN NOISE ATTACKS Nose parameters (%) PSNR(dB) NC ) JPEG attacks. JPEG compresson process s done by usng the percentage of mage qualty as a parameter to measure. The watermarked text mage wth PSNR=17.71dB under JPEG attacks (10%) s shown n Fg4. the watermarkng can obvously be extracted wth NC=0.93. As shown n Fg. 4. Table Ⅲ shows the NC values between the extracted and embedded watermarkng and the PSNR of the attacked watermarked mage. Fgure 3. The watermarked text mage under Gaussan nose attacks(10%). the watermarked text mage under nose attack. the extracted watermarkng Fgure 4. The watermarked text mage under JPEG attacks (10%). the watermarked text mage under JPEG attacks. the extracted watermarkng.. TABLEⅢ THE PSNR AND NC UNDER JPEG 571

5 Compresson Qualty(% ) PSNR(dB) NC B. Geometrcal attacks. 1) Rotaton attacks. We nvestgate the effectveness of our proposed watermarkng algorthm aganst rotaton angle as the parameter. The watermarked text mage under rotaton attacks (clockwse by 5 ) wth PSNR=6.31dB under rotaton attacks s shown n Fg. 5. The watermarkng can obvously be extracted wth NC=0.76. As shown n Fg. 5. Table Ⅳshows the NC values between the extracted and embedded watermarkng and the PSNR of the attacked watermarked mage. Fgure 5. The watermarked text mage under rotaton attacks. (clockwse by 5 ). the watermarked text mage under rotaton attacks. the extracted watermarkng.. TABLE Ⅳ THE PSNR AND NC UNDER ROTATION ATTACKS Rotaton (clockwse) PSNR(dB) NC Can be seen the extracted watermarkng s very smlar to the orgnal watermarkng. ) Scalng attacks. We use the scalng factor as parameter to valdate the effectveness of our proposed algorthm on dfferent scalng attacks. When the watermarked mage s scaled 0.5 tmes ts pxel pont has become a quarter of the orgnal. The resoluton has sent a lot of. Fg. 6 shows that the watermarked mage shrunk wth a scale factor of 0.5. Moreover Fg. 6 shows that the watermarkng can be extracted wth NC=1.0. Table Ⅴ shows the NC values between the extracted and embedded watermarkng wth scalng attacks on the watermarked mage wth multple scale parameters. Fgure 6. The watermarked text mage under scalng attacks. (0.5 tmes). the watermarked text mage under scalng attacks. the extracted watermarkng. TABLEⅤ THE NC UNDER SCALING ATTACKS Scalng factor NC V. CONCLUSION Many watermarkng algorthms exst for the frequency doman usng ether the DCT or the DWT. In ths paper we propose a new watermarkng algorthm usng the DWT pror to the DCT to provde better mperceptblty n harmony wth the human vsual system. Experments show that ts robustness s better than DWT or DCT algorthm alone after applyng the same attacks. In addton t can be used to mprove the PSNR and enable to blnd extracton. ACKNOWLEDGEMENT Ths work s supported by the Natonal Natural Scence Foundaton of Chna (No: ) and the Insttutons of Hgher Learnng Scentfc Research Specal Proect of Hanan (Hnkyzx014-)and the Internatonal Scence and Technology Cooperaton proect of Hanan (No: KJHZ014-16) and the Key Scence and Technology Proect of Hanan (No: ZDXM ). REFERENCES [1] Alar Kuusk Enar Relent Ivor Loobas Marko Parve "Software Archtecture for Modern Telehealth Care Systems" AISS Vol. 3 No. pp. 141 ~ [] Xuemng L Guangun He "Effcent Audo Zero-Watermarkng Algorthm for Copyrght Protecton Based on BIC and DWCM Matrx" IJACT Vol. 4 No. 6 pp. 109 ~ [3] Al AI-Ha "Combned DWT-DCT Dgtal Image Watermarkng" Journal of Computer Scence 3(9): [4] M. Unok R. Myauch Reversble Watermarkng for Dgtal Audo Based on Cochlear Delay Characterstcs In Proceedngs of the 011 Seventh Internatonal Conference on Intellgent Informaton Hdng and Multmeda Sgnal Processng Oct. 011 pp [5] B.S.Manunath Gabor wavelet transform and applcaton to problems n computer vson n 6th Aslomar Conference on SgnalsSystems and ComputersPacfc GroveCAl99 PP [6] Xa X. G. Boncelet C. G. and Arce G.R. A multresoluton watermark for dgtal mages Proc. Int. Conf. on Image Processng 97 Santa Barbara CA U. S. A. Vol. I pp [7] Huang D Yan H. Interword dstance changes represented by sne waves for watermarkng text mages IEEE Trans. Syst. Vdeo Technol. 11(1)pp [8] Cox I Klan J Leghton T Shamoon T Secure spread spectrum watermarkng for multmeda IEEE Transactons on Image Processng6(1)pp [9] Hseh C. T. Lu Y. L. Luo C. P. and Kuo F. J. A study of enhancng the robustness of watermark Proc. IEEE Int. Sym. on Multmeda Software Engneerng Tawan pp [10] Ester Yen and L-Hsen Ln"Rubk s cube watermark technology for grayscale mages" Vol 37(6) pp Jun [11] GAO Xn-yu LV Jan-png. A block-based DCT algorthm of dgtal mage watermarkng.journal OF XI AN UNIVERSITY OF POSTS AND TELECOMMUNICATIONS.Vol.1 No.5 Sep