A Blind Image Watermarking Based on Dual Detector *

Transcription

1 JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 25, (2009) A Blind Imge Wtermrking Bsed on Dul Detector * CHIN-PAN HUANG 1, CHI-JEN LIAO 2 AND CHAUR-HEH HSIEH 1 1 Deprtment of Computer nd Communiction Engineering Ming Chun University Toyun, 333 Tiwn 2 Deprtment of Informtion Engineering I-Shou University Kohsiung, 840 Tiwn This pper presents blind imge wtermrking technique bsed on novel detection scheme which contins two detectors iming t the positive ttck nd negtive ttck, respectively. The nlysis on signl processing ttck indictes tht there exist unrelible trnsformed coefficients in the ttcked imge which result in errors of the extrction of wtermrk dt. The novel detection scheme removes the unrelible trnsformed coefficients nd employs the remining relible coefficients for the extrction of embedded wtermrk. The experimentl results indicte the proposed technique improves robustness significntly, s compred to the existing single detector scheme. Keywords: imge wtermrking, ttcks, discrete cosine trnsform, robustness, dul detector 1. INTRODUCTION Digitl wtermrking cn prove to be useful to void the illegl use of digitl medi. Generlly, it cn be clssified into two types: robust wtermrking nd frgile wtermrking. The requirements for robust wtermrking re trnsprency, robustness, security, cpcity, universlity, nd unmbiguousness [1]. Among them, trnsprency nd robustness re most importnt. Trnsprency refers to the perceptul qulity of the imge being protected. In other words, the wtermrk should be invisible over the originl imge. Robustness refers to the bility to detect the wtermrk fter unintentionl ttck, i.e., common signl processing opertions [2]. The technique presented in this pper belongs to the robust type. Depending upon work domin tht wtermrk is embedded in, wtermrking techniques cn be clssified into two ctegories: sptil domin nd trnsform domin [3-15]. Recent efforts re mostly bsed on trnsform-domin becuse it offers better robustness. According to whether the host signl is needed or not during the detection, wtermrking technique cn be roughly ctegorized into two types: non-blind nd blind [16]. Non-blind method requires the originl host in the detection end, wheres blind one does not. The blind methods re more useful thn non-blind becuse the host imge my be not vilble in rel-world scenrios. Generlly, blind methods re often less robust nd lso hrder to implement thn non-blind ones. Mny blind imge wtermrking schemes [16-22] hve been presented recently. Received Februry 26, 2008; revised June 9 & August 4, 2008; ccepted August 22, Communicted by H. Y. Mrk Lio. * This pper ws prtilly supported by the Ntionl Science Council of Tiwn, R.O.C., No. NSC E

2 1724 CHIN-PAN HUANG, CHI-JEN LIAO AND CHAUR-HEH HSIEH The existing blind schemes cn be roughly clssified into three types [16]: () correltion-bsed; (b) bsed on bsolute modultion of individul primry or secondry elements of n imge; (c) bsed on reltive modultion of pir elements. Most of these schemes focus on embedding strtegy. In ddition, they do not exploit the chrcteristics of the ttcks. In this work, we im t the design of n efficient detection scheme tht tkes signl processing ttcks into ccount. Detection is n inverse process of embedding. Most detection schemes of trnsform-domin wtermrking in the literture use ll trnsformed coefficients of the test ttcked imge to extrct wtermrk. In this pper, the nlysis on the ttcked imges indictes tht there re unrelible trnsformed coefficients which would yield the extrction error of wtermrk dt. To ttck the problem, we develop new detection scheme tht removes the unrelible trnsformed coefficients. The new detection contins two detectors tht re bsed on positive ttck (PA) nd negtive ttck (NA), which re obtined through nlyses nd experiments. The proposed dul-detector scheme is different from the cocktil wtermrking [15] which lso employs two detectors. The cocktil wtermrking is non-blind scheme which embeds two complementry wtermrks, clled positive hiding (PH) nd negtive hiding (NH), into the host imge simultneously. In detection, two corresponding detectors re used to extrct PH nd NH wtermrks. In such cse, t lest one wtermrk survives when ny ttcks occurs. Therefore, the missed detection rte will be reduced nd thus improving robustness significntly. However, if no wtermrk is embedded into the host imge nd the imge suffers from positive ttck or negtive ttck, our previous study [23-25] indicte tht cocktil method will introduce high flse lrm rte. Unlike the cocktil method, in this work we embed only one wtermrk, nd design two detectors to rise the detection rte of wtermrk. These two detectors re minly bsed on chrcteristics of ttcks, which re not directly relted to the embedding scheme like cocktil pproch. The other difference between the cocktil method nd this work is the cocktil scheme [15] is non-blind one. The remining sections re orgnized s follows. The proposed wtermrking system is described in section 2. A single detector lgorithm is first presented. Then novel dul detector scheme bsed on ttck chrcteristics is developed. In section 3, experimentl results with single detector nd our dul detector methods re provided. The conclusions re drwn in section PROPOSED BLIND WATERMARKING The proposed wtermrking system is shown in Fig. 1. The host imge is trnsformed by full-domin DCT. The DC coefficient is discrded, nd the remining twodimensionl AC coefficients re converted into one-dimensionl coefficient sequence F(k) vi zig-zg scnning. The binry wtermrk is embedded into the coefficient sequence. In the detection end, the received wtermrked imge is trnsformed with DCT s in the embedding end, nd the resulting AC coefficients re fed into positive-ttck detector nd negtive-ttck detector simultneously. The lrger response of the two detectors is input to thresholding device. If it is greter thn the detection threshold ρ t, we clim tht the wtermrk exists; otherwise, the wtermrk does not exist. The designs of embedding nd detection re performed on the bove AC coefficient sequence, nd the design detils re described in the following.

3 A BLIND IMAGE WATERMARKING 1725 () Embedding. (b) Detection. Fig. 1. Proposed blind wtermrking system. 2.1 Embedding We clculte reference (estimte) sequence from the AC coefficient sequence F(k) by slide window of (2m + 1); i.e. m F( k) = sign( F( k)) 1 F( k+ j). (1) (2 + 1) m j= m In this work, the slide window length is 5 (m = 2). The binry wtermrk W i is embedded by the following rule: F ( k) = F( k) + sign( W ) α F( k) (2) m i where α is hiding fctor with the vlue between 0 nd 1 (in this work, α = 0.5), sign(x) is sign function, nd F m (k) is the resulting signl with wtermrk embedded. In Eq. (2), if the wtermrk bit to be embedded is 1, F m (k) is the sum of the reference Fk ( ) nd positive embedded energy α F( k) ; otherwise, if the wtermrk bit is 1, F m (k) is the difference of the reference nd α F( k). In detection, the wtermrk cn be esily extrcted by e m m W () i = sign( F ( k) F ( k)). (3) More specificlly, if Fm( k) > Fm( k), the extrcted wtermrk bit is 1; otherwise it is 1. In the bove eqution, Fm ( k ) is the DCT coefficient sequence of the test imge which suffered from ttck; Fm ( k ) is its corresponding reference coefficient sequence, which is clculted using the estimtion scheme in Eq. (1). The bove detection scheme hs been widely used in most blinding wtermrking techniques, which doesn t consider the

4 1726 CHIN-PAN HUANG, CHI-JEN LIAO AND CHAUR-HEH HSIEH ttck chrcteristics. It employs one detector only, so we refer to it s single detector for comprison purpose. In generl, the length of wtermrk sequence, B L, is much smller thn tht of the medi to be embedded (the AC coefficient sequence), M L. To increse the security nd prevent interction between the successive embedded dt, we expnd rndomly the originl binry wtermrk strem, sequence of {+ 1, 1}, into ternry strem, sequence of {+ 1, 1, 0}. The coefficients corresponding to the symbol 0 re not embedded with wtermrk messge. The length of the ternry strem, T L, is obtined ccording to the rnge of the AC coefficient to be hidden. T L is lrger thn B L but smller thn M L. Fig. 2 illustrtes the pseudo-rndom expnsion using simple exmple, in which wtermrk sequence with length of 3 bits is mpped into ternry strem with length of 10 symbols. It is seen tht the originl wtermrk bits re permuted in the ternry strem. Through this mnner, short wtermrk sequence cn be embedded in long AC coefficient sequence in pseudo-rndom wy, which is controlled by key. Binry wtermrk { 1, + 1} W 0 W 1 W 2 Ternry sequennce{0, 1, + 1} 0 W W W 2 0 Fig. 2. Wtermrk expnsion from binry symbol to ternry symbol. 2.2 Detection As mentioned erlier, detection is n inverse process of embedding. Thus it does not consider the chrcteristics of the ttcks. This pper ims to develop new detection scheme which tkes ttcks into ccount. The ttcks cn be clssified into three ctegories: positive ttck (PA), negtive ttck (NA) nd hybrid ttck (HA) nd they re not imge dependent. Note tht the hybrid (rndom) ttck cn be regrded s combintion of positive nd negtive ttck. The detils of chrcteristics of these ttcks cn be found in our previous works [23-25]. The new scheme ctegorizes the ttcks into positive ttck (PA) nd negtive ttck (NA) nd then design two detectors ccordingly. We cll the detection scheme s dul detector for convenience. The scheme is designed minly bsed on the nlysis of the typicl imge processing ttcks in Tble 1. The ttcks correspond to the signl processing ctegory (noise nd convo filter) of StirMrk benchmrk [21]. Here we summrize the chrcteristics of the ttcks in the following, which re relted directly to this work. The detils cn be found in [24, 25]. Ech signl processing ttck yields in both positive modultion (PM) nd negtive modultion (NM) to the host imge [15, 23-25]. PM (NM) denotes tht the mgnitude of n AC coefficient of the ttcked imge is greter (less) thn tht of the unttcked imge. To chrcterize the ttcks, we employed two mesures to investigte the chrcteristics of the AC coefficient sequence F(k). One is the verge coefficient mgnitude chnge rtio (AMR) before nd fter ttck, nd the other is occurrence frequency (OF) before nd fter ttck. The former mesures the verge ttck energy for whole imge, nd

5 A BLIND IMAGE WATERMARKING 1727 Tble 1. Imge processing ttcks. Imge Processing Functions nd clssifictions 01- Averge (7 7) NA 08- Enhnce Edges (75) PA 02- Blur (75) NA 09- Enhnce Focus PA 03- Gussin Blur (7 7) NA 10- Focus Restortion PA 04- Soften (75) NA 11- Shrpen (50) PA 05- JPEG compression (75) NA 12- Rndom Noise (±16) HA 06- JPEG compression (25) NA 13- Rndom Noise (±8) HA 07- Enhnce Detil PA AMR PA NA AC Coefficient Set 100 () AMR OF (%) 50 PA NA AC Coefficient Set (b) OF. Fig. 3. Results of shrpening opertion.

6 1728 CHIN-PAN HUANG, CHI-JEN LIAO AND CHAUR-HEH HSIEH AMR PA NA AC Coefficient Unit 100 () AMR OF(%) 50 PA NA AC Coefficient Set (b) OF. Fig. 4. Results of JPEG compression. the lter evlutes the number of coefficients ttcked (clled ttck frequency). Fig. 3 shows the two mesures when imges re suffered from shrpening ttck. The figure compres the two mesures for PM nd NM, respectively. It is obvious tht for the shrpening opertion, PM domintes both in ttck energy nd ttck frequency. Therefore, it is clssified s positive ttck. On the contrry, s seen in Fig. 4, for JPEG compression, NM domintes, thus it is regrded s negtive ttck. Using the two mesures, ll signl processing ttcks cn be clssified. Positive ttck will move the embedded coefficients wy from the reference vlue. Thus the ttcked signl is more robust to noise thn the unttcked one. So positive t-

7 A BLIND IMAGE WATERMARKING 1729 tck is helpful for extrction of wtermrk. On the contrry, negtive ttck will pull embedded coefficients such tht they re close to the reference vlue. In this cse, even smll noise my cuse the signl jumping from bove (or below) reference to below (bove) reference, which yield the error of extrction of wtermrk. The dynmic rnge (the difference between positive reference nd negtive reference) becomes lrger fter positive ttck nd smller fter negtive ttck. Furthermore, for negtive ttck, when ttck energy is high, ll the coefficients my be reduced to pproximte zero vlue. In such cse, the detection of wtermrk would fil. So, it is resonble to sy tht if the vlue of coefficient is very smll, the coefficient is probbly suffered from lrge negtive ttck. Therefore, it is not relible nd should not be used for the detection. As mentioned before, some of the coefficients of the ttcked imge re not relible. The unrelible coefficients should not be included for wtermrk extrction; otherwise, it will yield errors of extrction. In this work, we present novel detection scheme tht removes the unrelible coefficients nd uses the remining relible coefficients for extrction of wtermrk. It contins two detectors tht exploit the chrcteristics of positive ttck nd negtive ttcks, respectively. 2.3 Dul Detector For convenience, we define n ttck mgnitude devition rtio s R(k) = ( Fm ( k) Fm()/ k Fm(). k If no ttck exists, it is esy to obtin R(k) = α from Eq. (2). Therefore, if R(k) > α we cn sy tht positive ttck occurs; otherwise, negtive ttck occurs when R(k) < α. The decision rule is suited for the idel cse in which the reference Fm ( k ) is fixed vlue. However, our investigtion indictes tht Fm ( k ) my fluctute slightly with different k nd different ttcks. To void the clssifiction error of ttck types, we nrrow down the PA rnge by introducing the prmeter β which is lrger thn α. Specificlly, if R(k) > β (β > α), the ttck is regrded s positive. Bsed on the concept, we design detector for extrcting the coefficients suffered from positive ttck s follows. Unlike most techniques in the literture, the detectors of our technique re designed ccording to the types of mplitude ttcks mentioned bove, rther thn the corresponding embedding scheme. Positive Attck Detector: The wtermrk is extrcted by 1, if R( k) > β nd sign( Fm( k) Fm( k)) = sign( Fm( k)) > 0 e Wp () i = 1, if R( k) > β nd sign( F ( ) ( )) sign( ( )) 0. m k Fm k = Fm k < 0, otherwise (4) The rule in the top line of Eq. (4) is for positive coefficients (the sign of the coefficient is positive) of the received signl, wheres the rule in the middle line is for negtive coefficients. The extrcted wtermrk bits for unrelible coefficients re set to zero (bottom line of Eq. (4)) such tht they re useless in the clcultion of detection response. The

8 1730 CHIN-PAN HUANG, CHI-JEN LIAO AND CHAUR-HEH HSIEH ction is equivlent to removing the unrelible coefficients for detection of wtermrk. The extrcted wtermrk bits for the relible coefficients re + 1 or 1. It is obvious tht the detector output contins three symbols: + 1, 1, nd 0. This is unlike the conventionl detection scheme in which two symbols (+ 1 nd 1) re employed. The detector response (normlized correltion) between the originl wtermrk strem nd extrcted wtermrk strem under positive ttck is defined s ρ e e p mm, p W Wp = e p Wi () W () i (, ). Wi ( ) W( i) (5) The denomintor is the totl number symbols of + 1 nd 1 extrcted. As mentioned before, negtive ttck my mke the R very smll, or the reference vlue close to zero. In either cse, the extrction of wtermrk is unrelible becuse it is sensitive to noise. In order to rise the relibility of wtermrk extrction, we remove the unrelible coefficients tht stisfy R(k) < ε or Fm ( k) < σ, nd thus obtin the negtive ttck detector in the following. Negtive Attck Detector: The wtermrk is extrcted by e sign( F ( ) ( )), if ( ) nd ( ) () m k Fm k ε R k β Fm k σ Wn i = < < >. 0, otherwise (6) Like the positive ttck detector, the bottom line in Eq. (6) is used to remove the unrelible coefficients. The detector output lso contins three symbols: + 1, 1, nd 0. The normlized correltion between the originl wtermrk strem nd extrcted wtermrk strem under negtive ttck is defined s ρ mm,n, using the sme eqution s in Eq. (5) but replcing the positive extrction prmeter W () i with W (). i The lrger of the bove two detection responses, mx{ρ mm,p, ρ mm,n }, is used to judge whether the wtermrk is present or bsent by compring it with predefined detection threshold (ρ t in Fig. 1). If it is greter thn the threshold, the wtermrk exists; otherwise, it doesn t exist. It is seen from Eq. (4) tht if β is set higher, more coefficients would be regrded s unrelible; consequently, it my reduce flse lrm rte, wheres increse missed detection rte. On the other hnd, if β is set lower, fewer coefficients would be regrded s unrelible, which my increse flse lrm rte while reduce missed detection rte. Thus, the vlue of β is determined by tking the compromise of flse lrm nd missed detection. Similr conclusion is pplied for the determintion of the vlues of ε nd σ in Eq. (6). In ddition, the vlues of prmeters ε nd β depend on the vlue of α. The reltionship is hrd to chieve theoreticlly. Our experience indictes tht β 1.25α nd ε 0.75α re good choices. In ddition, the threshold σ is determined experimentlly nd σ = 20 is lso good choice. e p e n

9 A BLIND IMAGE WATERMARKING SIMULATIONS The experiments re conducted on 50 test imges with size of from IM- AGEMORE Coopertion [22]. A binry wtermrk length with length of 1024 is obtined by generting zero-men pseudo-rndom sequence with length of 1024, nd then tking the sign of ech dt point of the sequence. The binry wtermrk is expnded into ternry strem with length , nd then modulted into the host imges. Thirteen types of imge processing ttcks (listed in Tble 1) including positive (e.g., shrpening), negtive (e.g., blurring) nd hybrid ttcks, re pplied to the test imges, respectively, nd thus totlly 650 ttcked imges re obtined. The hiding fctor is chosen s α = 0.5, which yields good embedded picture qulity. Fig. 5 demonstrtes some typicl imges embedded with wtermrks. The detection prmeters ε nd β re chosen experimentlly s ε = 0.2 nd β = 0.7. Note tht the mgnitude of n AC coefficient is generlly relted to its frequency bnd. The smll coefficient corresponds to higher frequency bnd nd its effect is t the detil of n imge. Although the smll coefficient in lower bnd my chnge reltive lrge vlue, it is very rre from experiences of our experiments. It is cler tht the smll coefficient cuses very limited effect on qulity of the wtermrked imge so tht the imge qulity cn be gurnteed. Fig. 5. Typicl imges embedded with wtermrk. The test imges re used to evlute the single detector nd our proposed dul detector scheme. The comprison of the two detection schemes is in terms of flse negtive rte (missed detection rte) nd flse positive rte (flse lrm rte). The former corresponds to robustness, nd the lter to flse lrm. The two performnces conflict ech other. More specificlly, in detection, when the detection threshold (ρ t in Fig. 1) is set higher, the flse lrm rte cn be reduced, but the flse negtive rte will become higher. In rel pplictions, compromise needs to be tken by choosing n pproprite detec-

10 1732 CHIN-PAN HUANG, CHI-JEN LIAO AND CHAUR-HEH HSIEH tion threshold vlue. Becuse the two mesures conflict, we use the totl error rte (the sum of the two error rtes) s the performnce metric. The smller the totl error rte, the better the system performnce. Tble 2 lists the totl error rtes of the two schemes for vrious vlues of detection threshold. It indictes the totl error rte of our dul detector scheme is less thn one hlf of the single detector scheme. The result cn be confirmed from ROC (receiver operting curve) performnce comprison in Fig. 6. Tble 2. Performnce comprison of single detector nd dul detector under vrious threshold vlues. Threshold vlues Methods Single Detector Dul Detector Criteri Missed detection rte Flse lrm rte Totl error rte Missed detection rte Flse lrm rte Totl error rte Fig. 6. The ROC performnces of single detector nd dul detector. Fig. 7. The error rtes vs. detection threshold vlues for single detector. Fig. 8. The error rtes vs. detection threshold vlues for dul detector.

11 A BLIND IMAGE WATERMARKING 1733 Figs. 7 nd 8 show the curves of the two error rtes under vrious detection threshold vlues. The figures provide the cue for the selection of pproprite threshold vlues to meet the requirements of users. It is seen from Fig. 8 tht if threshold is set in the rnge of 0.2 to 0.3, the dul detector gives pproximte zero missed detection nd flse lrm rtes. However, Fig. 8 indictes tht the single detector definitely yields errors (either missed detection or flse lrm or both) whtever the threshold vlues re chosen. Obviously, the dul detector is better thn single detector even from the viewpoint of threshold selection. 4. CONCLUSIONS A blind imge wtermrking technique bsed on the chrcteristics of mplitude ttcks hs been proposed. In the novel method, two detectors re designed which im t extrcting relible trnsformed coefficients under positive ttck nd negtive ttck, respectively. The removl of unrelible coefficients is very useful to reduce the error of wtermrk extrction. The results indicte tht our scheme performs much better thn the single detector tht uses ll the trnsformed coefficients nd does not consider the ttck chrcteristics. The system presented here is just for demonstrting the benefit of the novel detection scheme. It could be pplied to other trnsformtions such s discrete wvelet trnsform [26, 27]. Furthermore, the proposed detection scheme cn be pplied to ny existing wtermrking systems to further improve their performnces. The mjor limittion of our scheme is tht the determintion of prmeters vlues is performed experimentlly. An utomtic clcultion mechnism for the prmeters my be worth further investigting in the future. REFERENCES 1. F. Hrtung nd M. Kutter, Multimedi wtermrking techniques, Proceedings of IEEE, Vol. 87, 1999, pp I. J. Cox, M. L. Miller, nd J. A. Bloom, Digitl Wtermrking, Morgn Kufmnn Publishers, Los Altos, CA, S. Ktzenbeisser nd F. A. P. Petitcols, Informtion Hiding Techniques for Stegnogrphy nd Digitl Wtermrking, Artech House, Boston, London, M. Bender, D. Gruhl, N. Morimoto, nd A. Lu, Techniques for dt hiding, IBM System Journl, Vol. 35, 1996, pp N. Nikolidis nd I. Pits, Copyright protection of imges using robust digitl signtures, in Proceedings of IEEE Interntionl Conference on Acoustics, Speech, nd Signl Processing, 1996, pp R. B. Wolfgng nd E. J. Delp, A wtermrk for digitl imges, in Proceedings of Interntionl Conference on Imge Processing, Vol. 3, 1996, pp I. J. Cox, J. Kilin, F. T. Leighton, nd T. Shmoon, Secure spred spectrum wtermrking for multimedi, IEEE Trnsctions on Imge Processing, Vol. 6, 1997, pp C. I. Podilchuk nd W. Zeng, Imge-dptive wtermrking using visul models,

12 1734 CHIN-PAN HUANG, CHI-JEN LIAO AND CHAUR-HEH HSIEH IEEE Journl on Selected Ares in Communictions, Vol. 16, 1998, pp A. Piv, M. Brni, E. Brtoloni, nd V. Cppellini, DCT-bsed wtermrking recovering without resorting to the uncorrupted originl imge, in Proceedings of IEEE Interntionl Conference on Imge Processing, Vol. 1, 1997, pp C. T. Hsu nd J. L. Wu, Multiresolution wtermrking for digitl imges, IEEE Trnsctions on Circuits nd Systems II: Anlog nd Digitl Signl Processing, Vol. 45, 1998, pp S. H. Wng nd Y. P. Lin, Wvelet tree quntiztion for copyright protection, IEEE Trnsctions on Imge Processing, Vol. 13, 2004, pp C. S. Lu nd H. Y. M. Lio, Multipurpose wtermrking for imge uthentiction nd protection, IEEE Trnsctions on Imge Processing, Vol. 10, 2001, pp C. W. Tng nd H. M. Hng, A feture-bsed robust digitl imge wtermrking scheme, IEEE Trnsctions on Signl Processing, Vol. 51, 2003, pp A. M. Ahmed nd D. D. Dy, Applictions of the nturlness preserving trnsform to imge wtermrking nd dt hiding, Digitl Signl Processing, Vol. 14, 2004, pp C. S. Lu, C. J. Sze, nd H. Y. M. Lio, Cocktil wtermrking for digitl imge protection, IEEE Trnsctions on Multimedi, Vol. 2, 2000, pp Y. Wng nd A. Perlmn, Blind imge dt hiding bsed on self reference, Pttern Recognition Letters, Vol. 25, 2004, pp C. Jing, M. Yu, S. Shi, X. Liu, nd Y. D. Kim, New blind imge wtermrking in DCT domin, in Proceedings of Interntionl Conference on Signl Processing, Vol. 2, 2002, pp M. K. Mihck nd R. Venktesn, Blind imge wtermrking vi derivtion nd quntiztion of robust semi-globl sttistics, in Proceedings of IEEE Interntionl Conference on Acoustics, Speech, nd Signl Processing, Vol. 4, 2002, pp J. J. Eggers, J. K. Su, nd B. Girod, Robustness of blind imge wtermrking scheme, in Proceedings of IEEE Interntionl Conference on Imge Processing, Vol. 3, 2000, pp Y. Hu, W. Q. Lid, Y. Deng, W. He, nd J. Di, Redble wtermrking lgorithm bsed on wvelet tree quntiztion, in Proceedings of Interntionl Conference on Communictions, Circuits nd Systems, Vol. 1, 2004, pp C. J. Lio nd C. H. Hsieh, A new digitl imge wtermrking method bsed on complementry detectors, in Proceedings of the 17th Conference of Computer Vision, Grphics, nd Imge Processing, Vol. E3-4, C. H. Hsieh, C. J. Lio, nd J. C. Tsi, Anlysis of mplitude ttck in imge wtermrking system, in Proceedings of Interntionl Symposium on Communiction, C. H. Hsieh nd C. J. Lio, A novel imge wtermrking scheme bsed on mplitude ttck, Pttern Recognition, Vol. 40, 2007, pp N. Kewkmnerd nd K. R. Ro, Wvelet bsed imge dptive wtermrking scheme, Electronics Letters, Vol. 36, 2000, pp

13 A BLIND IMAGE WATERMARKING J. J. K. O. Runidh, W. J. Dowling, nd F. M. Bolnd, Phse wtermrking of digitl imges, in Proceedings of IEEE Interntionl Conference on Imge Processing, Vol. 3, 1996, pp Chin-Pn Hung ( ) ws born in 1959 in Tiwn, R.O.C. He received the B.S. nd M.S. degrees in Electricl Engineering from Chung Cheng Institute of Technology, Tiwn, in 1981, in 1985, respectively. In 1996, he received the Ph.D. degree in Electricl Engineering from University of Pittsburgh, Pittsburgh, PA, U.S.A. In , he ws n ssocite scientist of Electronic System Division in Chung Shn Institute of Science nd Technology. He then joined the deprtment of Computer nd Communiction Engineering t Ming Chun University in August 2002, nd is currently n ssistnt professor there. His recent reserch interests include dt compression, computer vision, digitl imge/signl processing, nd pttern recognition. Chi-Jen Lio ( ) ws born in Keelung, Tiwn. He received the mster degree in Deprtment of Informtion Engineering in 2004 from I-Shou University (ISU), Tiwn, R.O.C., where he is currently working towrd the Ph.D. degree. His mjor reserch interests include imge processing, wtermrking, color mngement nd imge qulity evlution. Chur-Heh Hsieh ( ) received Ph.D. degree in Electricl Engineering in 1990 from Chung Cheng Institute of Technology (CCIT), Tiwn, R.O.C. In 1981, He joined the fculty of the Deprtment of Electricl Engineering t CCIT, nd becme professor in From 1996 he joined I-Shou University (ISU) s full professor of Informtion Engineering Deprtment. In 1997, He developed reserch group for video nd imge processing t ISU. From 1999 to 2002, he served s the chirmn of the deprtment. He ws Visiting Scholr in the Deprtment of Electricl Engineering t University of Wshington from Februry to July in From 2007 he joined Ming Chun University s full professor of Computer nd Communiction Engineering Deprtment. His reserch interests include content-bsed imge/video retrievl, sport video nlysis, video understnding, dvnced video coding, imge wtermrking, sttisticl pttern recognition nd visul inspection. He hs published more thn 150 ppers in these subjects. Dr. Hsieh received Grde-A

14 1736 CHIN-PAN HUANG, CHI-JEN LIAO AND CHAUR-HEH HSIEH Reserch Awrds from Ntionl Science Council eleven times (from 1991 to 2001). In 2002, he received Outstnding Electricl Engineer Awrd, Kohsiung Chpter of The Chinese Institute of Electricl Engineering Society. He is reviewer of IEEE journls nd conferences s well s other leding interntionl journls. He hs served on the progrm committee of severl conferences nd workshops. He is n IEEE senior member. He is fellow of IET.