An Automatic Video-Object Based Steganographic System for Multi-Use Message Hiding Using Wavelet Transform

Klimis S . Ntalianis, Nikolaos D. Doulamis, Anastasios D. Doulamis, and Stefanos D. Kollias National Technical University of Athens, Dept. of Electrical & Computer Engineering

9, Iroon Polytechniou se., Zografou, Athens, 157-73, GREECE E-mail: kntal@iage.nhla.gr

Abstract- An automatic videoobject based steganographic system is proposed in this paper for multi- use message biding. Initially video objets from different images are selected and for each video object a message is embedded into its most significant wavelet coefiidents to provide invisibility and resistance against lossy tnnsmksion or otber distortion. The architecture conshts of three moduk. In the first moduk initial messages are enciphered using one or more encryption algorithms. The enciphered messages are imprinted onto white- background images to construct the messageimages to be hidden. In the second module each of tbe cover video objects is dwornposed into two levels with seven subband8 using the DWT. Next QualiFed Significant Wavelet Trees (QSWTs), which are paths of significaot wavelet coellicientg are estimated for the highest energy pair of subbands of each video object. During the third module each messageimage is redundantb embedded to the caellicients of the best QSWTs of a video object nnd the IDWT is applied to provide the stego-objed In the last stage stego-objects are combined to provide the fmal content to be transmitted. Experimental results under various loss rates indicate the robusbess and ellicieacy of the proposed stegaoograpbic system.

Kqworh: Video O b j d Steganographic System, QSWTs.

I. INTRODUCTION A significant interest for hiding and enciphering systems

has appeared during the last decade, mainly due to two reasons. Firstly, telecommunication and publishing indumies have become interested in biding copyright marks (watermarks) in digital media such as audio, video, docnments etc., foreseeing the urgent need for intellectual property protection. Secondly, decisions by various governments to consider stmng eocryption algorithms out of law have motivated people to study methods by which enciphered messages can be embedded in seemingly imocuo\s cover media [I]. Fwthermore the need for privacy and sufficient security in several applications such as e- bunking, mobile telephony, medical data interchanging etc., is rapidly increasing.

To confiord the content security problem cryptography and steganography were proposed, where c'yptographic algorithms scramble messages so that they cannot be understood, while steganographic methods hide messages so that they cannot be seen. Generally, steganagraphy utilizes the typical digital media such as text, images, audio or video

files as a carrier (called a host or cover signal) for hiding private information in such a way that unauthorized parties cannot detect or even notice its presence.

On the other hand the MPEG-4 standard introduced Video objects (VOs) which are semantic entities (e.g. a buman, a building etc.) ready for independent acquisition, editing, coding and distribution. These semantic entities make the produced content far more reusable and nexible, leading to a migration tiom hne-based to object-based consideration of digital media.

Several steganographic algorithms have been proposed in literature most of which are performed in pixel domain, where more embedding space (capacity) [Z] is provided Many of the existing approaches are based on Least Significant Bit (LSB) insenioq where the LSBs of the cover file are directly changed with message bits. Examples of LSE schemes can be found in [31, 141. LSB manipulation programs also exist for several image formats and can be faund in [5]. However, LSE methods are dnerable to extraction as pointed out in several works [61, [71, 181. Additionally LSE techniques are very seositive to image manipulations. For example convening an image from BMP to P E G and then back would deswoy the hidden information [6]. Furthermore if an enciphered message is LSE-embedded and transmitted over an error prone network then it may not be poss&le to decipher it, even in case of liule losses.

On the other hand, a limited number of methods to confront these problems has been proposed. In [9] spread spcxtnun image steganography (SSIS) was introduced. The SSIS incorporated the use of error control codes to correct the large numbcr of bit errors. In [IO] the message is hidden in the signhit values of insignificant children of the detail subbands in non-smooth regions of the image. Using this technique stegaographic messages can be send in lossy environments, with some robuslness against detection or attack. However low losses are considered and the problem of compression remains.

In this paper an efficient wavelet-based steganographic method is proposed for message hiding into video objects. The main advantages of the proposed system are: (a) hidden messages are perceptually invisible, statistically undetectable and thus difficult to extract, @) stegwbjects present significant resistance against lossy transmission since the message-image is embedded to their most significaat wavelet coefficients, (c) different messages can be created by synthesizing different stegodbjects to produce particular content and (d) several messages can be compactly transmitted and separately retrieved according to authorization privileges. In particular in the proposed system

0 2002 IEEE SMC TAlH3

Im rint Msssags-lmagcN(OU- Messagk N ( f i ) + - e b i T l

Stereoscopic Pairs- Video Objects Module Selection Estimation ? Extraction Module Video6batN

QSWTs Detection Module L ~

Module

QSWTs Detection Module L ~

Figure 1: System overview

the initial message is enciphered using one of the encwtion methods proposed in literature [Il l . Afternards the cipher- message is imprinted onto a white-background image to conmct the message-image to be hidden By imprinting the cipher-message onto an image, the amount of information to be hidden is reduced, hut the robuhless against transmission losses or other distortion increases substantially. Then a proper cover video object is selected according to the size of the fmal message and is decomposed into two levels by the separable 2-D wavelet transform, providing tJuw pain of subbands (HLa HL,), (Ma LH,) and (HH2, HH,): Next, the pair of subbands with the highest energy content IS detected and a Qualified Significant Wavelet Trees (QSWTs) approach similar to [I21 is proposed in order to select the coefficients where the final message should he casted. QSWTs, which are based on the defmition of the EZW algorithm [13], are bigbcnergy paths of wavelet coefficients and enable adaptive casting of the message-image energy in different resolutions, achieving resistant information embedding. Finally the message is redundantly embedded to both subhands of the selected pair, using a non-linear insertion procedun that adapts the messagc to the energy of each wavelet coefficient. Differences between the original and the stego-ohja are imperceptible to human eyes, while messages can be retrieved even under severe transmission losses. Experimental results exhibit the efficiency and robusmess of the proposed VO-based steganographic scheme. An overview of the proposed system is presented in Figure I .

11. QUALIFIED SIGNIFICANT WAVELET TREES (QSWTs)

By applying the DWT once to a video object, four parts of high, middle, and low frequencies (i.e. LL,, HL,, LH,, HH,) are produced, where subbands HL,, LH, and HH, contain the finest scale wavelet coefficients. The next coarser scale wavelet cwfficients can be obtained by decomposing and critically sub-sampling subband LL,. This process can be repeated several times, based on the specific application. Furthermore the original video object can be reconstructed using the IDWT. In the proposed steganographic scheme,

Coefficients with local information in the subbands are chosen as the target coefficients for hiding a message. Coefficients selection is based on QSWTs derived from EZW [I31 and the basic definitions are given below.

Fintly a parmt-child relationshp, is defmed between wavelet coefficients at different scales. corresponding to the same location. Excepting the highest fralumcy subhands (i.e. HL,, LH,, and HHI), every coefficient at a given scale can be related to a set of coefficients at the next finer scale of similar orientation. The coefficient at the come scale is called the parent, and all coefficients corresponding to the same spatial location at the next finer scale of similar orientation are called children. For a given parent, the set of all coefficients at all finer scales of similar orientation corresponding to the same location are called descendants.

Definition 1: A wavelet coefficient xn(i& D is a parent of xr,(p,q)). where D is a subband labeled XL., LH,, HH,.

Definition 2 If a wavelet coefficient x.(i,j) at the coarsest scale and its descendants x,&J satisfy k,,(ij)lTl, Lr..,(p,.q)l>T~ for given thresholds T, and T,, then x&) and its children are called a QSWT

p=tP2-1 Ii.2, g-j.2-lji*2,n>l, D 1 andp l .

111. TllE PROPOSED STEGANOGRAPHIC METHOD: IiIDIlriG STRATEGY AND

MESSAGE RECOVERY In the proposed stcganugnphic method one of the initial

steps includes finding the QSWTs for a pau of subbands of the cuver vidco oblect. Towads this direction let us w u m e that thc cover video object IS decomposed into WO L v C l S using the DWT to provide three pairs of rubbands: P,: ( H L , HL#) . P2: (LH,. LH,) and P,. (HH,. HH, ) . In the

Figure 2: Unsupe~sed emaction of the fmt cova video object. (a) Original left channel. @) Original right channel. (c) Color segments mask. (d) Depth segments mask. (e) Projection of the color segments onto the depth segments mask. (0 Fusion of the color segments belonging to the same depth segment. (s) Extracted foreground video object.

pmposed scheme the selected pair contains the high& energy content compared to the other two pairs. This can be expressed a.:

Select P; Ep, = mm(Ep,, E n , EpI), where

E p k = Y E [ x z ( i j ) I 2 + ~ ~ [x , (~J) ]~ , k=I.2,3 (I) p-1 PI!

with xz(iJ)ER. R={HLa LHA HHd, x~(p,&S. S=(HL,. LH,, HH,) and Mpix Npk is the size of one of the subbands at level 2.

A. The Hiding Strategy

After selecting the pair of subbank containing the highest energy content, QSWTs are found for this pair and the final message is embedded by modifying the values of the detected QSWTs. Let us assum without loss of generality that pair P,: QH2, Lff,) is selected. Initially the threshold values of each subband are estimated as:

~~

i=l j - I

Next QSWTs are detected according to the following algorithm:

Forj=l toMpl I* M~zxNp,isthesizeofsubbandLHz'l 1fx7/i.i)ZT,

Ft+l End If

End If End Forj

End Fori Afterwards swnmatiou of the coefficients of QSWT[i] for

i-0 to I is calculated and if the final message-image is of size axb then the top axb QSWTs (according lo summation) we selected for embedding the message. For this reason initially the gray levels of the fmal message-image are sorted in descending order prcducbg a gay-levels mahix. Then for i=l to axb the coefficients +CO of the gray-levels matrix are embedded as follows:

where x2(ij)ELHz, c2 is a scaling ,constant that balances unobsmcmess and robustness and x&' is a coefficient of the LH2 subband ofthe stego-object. This non-linear insertion

X ' k i J F X2(iJI*(l+CZX wfil)), (4)

. . . , Figure 3: Unsupavised extraction of the second mver video object. (a) Original lefl channel. @) Extracted foreground video object.

procedure is similar to [ 141 and adapts the message to the energy of each wavelet coefficient. Thereby when x&> is small, the embedded message energy is also small to avoid artifacts, while when xt(ij> is large the embedded message energy is increased for robustness, Similarly for the coefficients of subband LH, we have:

.. . 111 Finally the two-dimensional IDWT is applied to the

modified and unchanged subbands to form the stegoobject.

E. MrrsogeRecovery

Considering that the s t e g w b j m (or a distorted version of it) has reached its destination, the message-image is initially e x w e d by following a reverse to the embedding method process. Towards this direction let us assume that the recipient of the stego-object has also received the size of the message-image (axb), the scaling conslants (CI, cj) and possesses the original cover video object. Then the following Steps are performed in the recipient's side:

Stepl: Initially the received stegoabject X' and original video object X are decomposed into two levels with seven subbands using the DWT,

Y=DWTo() r m \-,

U'=DWf&) (7) Step2 Using the size of message-image (axb). the

embedded posihons are delccted by ~&OWI& the hidmg process deseribed in rubsenion 3.1. Then the coefftc~cnts of subband LH? (LHI) of Y are subtracted fmm the cocfbcnts of subband LH, (LH,) of Y and the result IS scaled down by thc value of coefficient of Lfl> (LII,) of Y, multiplied hy e, ( E , ) .

Fori=l t oaxb w:'qx;z'- x , q , (X,"l*C>) (8) W+(X :'I- X,"II (X,%,) (9) Sle 3 The resulting hidden message cocflicicnts w1("

and w!' are averaged and muranged to provide B e hidden message-imagc.

St~p4: The original message is recovered by decrypting the cnciphcmd mcssagc. impinled onto thc message-image.

1V. EXPERIMENTAL RESULTS The cffectivenes, and robusmess of the proposed video

oblect-based steganographic system har been exlens8vely cvaluatcd under v3nou1 ~CSIS, using real life wico ObJeCL?. In particular fmtly two cover video Objccts WCILI unsupxvlsedly extraced using the technique drscibed tn [ I SI. According to

this technique for a given stereoscopic pau of images a depth segments and a color segments map are initially produced, using stereoscopic analysis techniques and incorporating a segmentation algorithm. Then color segments are projected onto the depth segments map and fused according to their degree of overlap with the depth segments to extract the video objects. Video object e m t i o n results are depicted in Figure 2. In particular in Figures 2(a) and 2(b) the left and right channels of a stereoscopic pair of frames are depicted, while in 2(c) and 2(d) the color segments and depth segments masks are presented. Then in Figures 2(e) and 2(f~ projection of color segments onto the depth segments mask and color segments fusion are shown. Finally the extracted foreground video objecl is depicted in Figure 2@). The second COVR video object is shown in Figure 3, where the original left channel is presented in Figure 3(a) and the extracted foreground video object can be seen in 3@). In the performed experiments two messages were used to be bidden (one for each video object). The fmt, consisting of 35 characten (excluding spaces) was: "STEW OBJECTS FOR SECURE COMUUNICATIONS' and it was hidden to the video object of Figure 2(g). The s w n d message, consisting of 36 charanen was "STEGANOGWHY SUPPIEMEh'TS CRYPTOGWHY" and it was hidden to the video object of Figure 3@). For simplification purposes both messages were encipheted using a modified version of the Hill Cipher [I I]. However different algorithms can also be used, either to make messages more diSieult to be retrieved by unauthorized parties or to provide a layered message access according to different privileges (case of multiple content-recipients). The enciphelld messages were imprinted onto white-backgrourd images to provide the message-images. The message-image of the first case (32x88 pixels) can be seen in Figure 4(a), while the message-image of the second case (34x93 pixels) is presented in Figureqc).

Then according to the sires of the message-images, the top 32x88 QSWTs were selected for the fmt cover video object and the top 34x93 QSWTs were found for the second cover video object to embed the message-images. For simplicity in the performed experiments c, and cz were fued in all frequency bands and were chosen to be ci;o.l5 and c d . 2 . The stegwbjms can be seen in Figures 4@) and 4(d) respectively. As it can be observed the embedded messages have caused imperceptible changes to the video objects.

Next resistance of the pmposed system is investigated. Towards this direction initially the final content to be transmitted was created, by synthesizing the two stego- objects and a background video object without any hidden message.

FIEYRCNALMU FASDFJFDGIGU YEWCIBDFGRAI

(4

YWOURFOWFSL FllWHAFQWFAP STFASGTNQIERP

(4 (e) Figure 4: Final content generation (a) Message-image of the fmt case. @) Steg+object of the first case (PSM. 42.3 dB). (c) Message- image of the second case. (d) Stego+bject of the second case (PSNR: 445 dEl). (e) Synthesized fmal content using the two stegoubjects and a backgroundvideo object.

BERs.

Table 11: Message retrieval results for the stego-object of Figure 4(d), under different combinations of compression ratios and BERs.

The final content image i s depicted in Figure 4(e). This estimated for the stego-objects afler the performed image was then tested under different JPEG compression combinations of compression and lossy transmission. Finally ratios and Various Bit Error Rates (BERs). In particular in the two tables the retrieved messages are also presented compression ratios of 2.6. and 5.1 were used to decrease the As it can be observed even under heavy transmission losses mount of data. Then lossy transmission simulations were the retrieved messages are still clearly readable. performed for 3 different BERs of 3x104, IxIlT and 3 ~ 1 0 . ~ for the compressed fmal content image, considering that typical average BERs for cellular mobile radio channels are between IO and ID- [16]. Results of the message-images

for the fmt and second video objects are given in Tables I and II respectively. In these tables PSNRs have been

V. CONCLUSIONS AND DISCUSSION Security is one of the major factors to be considered when

designing communication nehuorks to exchange secret or personal information. SteganokFphy by does not

ensure secrecy but when combined with cryptography, more secure communication systems can be produced.

In this paper a wavelet-based stegaoographic system is proposed, which bides information in the most significant wavelet-cwfficient trees (QSWTs) of cover video objects. Hidden messages are perceptually invisible, statistically undetectable and thus difficult to extract The systems main aim is to provide resistance of the hidden messages under compression and transmission losses, in c o n a t to most existing systems that focus on capacity issues. For this reason the enciphered message is first imprinted onto a white- background image before being embedded to the cover video object. The produced fml content to be transmitted can be synthesized using one or more stegwbjects and other plain video objects. The fml content-image presents more robustness against losses or other distortion since content is synthesized and not predetermined as in other systems. Funhermore multiple messages can be transmitted and separately retrieved according to autholization privileges, by synthesizing different stegwbjects. The systems performance has been evaluated under several combinations of compression ratios and transmission losses, providing very promising results. Funhemore, it should be mentioned that in the performed experiments text messages have been considered. Nevertheless any type of digital media (e.g. binary/ peyscale/color images, audio, graphics etc.) can be hidden by d i n g minor modifications to the proposed system.

In fume research, oblivious message retrieval methods should be implemented and the problem of increasing information capacity of the final content should also be investigated in more detail.

VI. ACKNOWLEDGEMENTS The authors wish to thank MI. Chas Girdwood, for

providing the stereoscopic sequence Eye to Eye, produced in the framework of ACTS MIRAGE project and Dr. Siegmund Pastoor for providing the stereoscopic video sequences of the DISTIMA project. This research is funded by the State Scholarships Foundation of Greece.

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