Dual Domain Watermarking in the Biological

Color Model

David Nino*, Moussa Abdallah+, and Bassam Hammo°*° King Abdullah II School of Information Technology

Jordan University, Amman, 11942, Jordan*Email: daoud8Ogmail.com°Email: b.hammogju.edujo

+King Abdullah II School of Electrical EngineeringPrincess Sumaya University, Amman, 11941, Jordan

Email: moussagpsut.edujo

Abstract-In this paper we propose a novel method forwatermarking. It uses the spatial and the Discrete CosineTransform (DCT) Domains. The proposed method deals withcolored images in the biological color model, the Hue,Saturation, and Intensity (HSI). The method robustness istested against several attacks. Watermark security is increasedby using the Hadamard transform matrix. The watermarksused are meaningful, and of varying sizes.

Keywords HSI, DCT, Watermarking, Dual Domain.

I. INTRODUCTION

T HE need for mechanisms to protect ownership of digitalmedia is increasingly being emphasized since the

phenomenal growth of internet and networked multimediasystems. The active and vast research in watermarkingtechniques has been justified by the existence of forgedidentical copies of multimedia data.

Digital watermarking is the process in which data(watermark) is embedded into a multimedia object (coverwork) such that the watermark can be detected or extractedlater to make a declaration about the object [1].

Several classifications of watermarking techniques wereadopted. According to the need of the original watermark atextraction stage, watermarking can be classified into: atechnique that needs only the watermarked object and thewatermark key (if used at embedding) to be given to theextractor, and a technique that needs the original imageand/or the watermark itself. They are called blind andnonblind respectively [2].

Another way depends on how to embed the watermark. Itcan be embedded in the spatial domain, where embedding isdone directly into the cover. Or it can be in the transformdomain, such as Discrete Cosine Transform (DCT) orDiscrete Wavelet Transform (DWT).A third way classifies the watermark to be either visible or

invisible (imperceptible) in the resulting watermarked image[1].

In this study, we investigate a watermarking system in theHSI color model, in other words the biological system. It isreferred to as biological model because it deals with colorsin the same way that humans do, by describing the colors,and not giving statistics about the amount of this color orthat from which the resulting color is formed [3].

The HSI color space, also called HSL or HLS, stands forHue, Saturation, Intensity / Lightness. HSI color spacedetaches the intensity, which is the most useful descriptor ofmonochromatic images and a key factor in describing colorsensation, from the color-carrying information (hue andsaturation) in a color image [3].HSI color model has several advantages over the RGB

(red, green, and blue) model. In the RGB color model, red,green, and blue color components are highly correlated,therefore RGB is not ideal for all applications and difficultto execute some image processing algorithms [4]. Thismakes the HSI color model ideal for developing algorithmsbased on color description [3].

Information hiding techniques, watermarking in specific,is being investigated vastly since the first academicconference on this topic in 1996 [5]. Early beginnings ofwatermarking were in the spatial domain, and have evolvedto the transform domains such as the DCT and DWT, for theincreased properties in these domains over the spatial.

Reference [6] presents a block based spatial watermarkingmethod. This method inserts watermark information using asecret key in a digital image. The process decomposesimages spatially into blocks, and classifies pixels inhomogeneous luminance zones. Embedding is done in theorder relationship between mean values inside the zones.This method introduces no artifacts for JPEG compressionof quality factor 7500. Our method transforms the image tothe frequency domain in a block wise manner, not pixelwise. Embedding is done in the mid band frequency of theDCT block.

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Dual watermarking was proposed in [1]; the duality comesfrom the visible and invisible watermarks embedded in thecover image in the DCT domain. This method protects bothownership and authenticity of the images. The dualityproposed by our system totally differs from the oneproposed in [13]. We mean by duality, both the spatial, andfrequency domains.

In 2001 Maity [7], proposed a robust, computationallyefficient and blind digital image watermarking in spatialdomain. The used watermark is meaningful andrecognizable. Results of robustness to different signalprocessing operations are found to be satisfactory.

In 2004 Al-Omari [8], embeds a watermark in the DCTdomain after truncating the DCT coefficients to the nearestinteger. As most of the systems provided in the literature thatwork in the DCT domain. It neglects the decimal part for theDCT coefficients. Now at the level of each block with blocksize equal to 8 x 8, Al-Omari embeds 8 bits/block in thehighest DCT coefficients in each block.

In 2006 Abdel-Majeed [9], enhanced the methodproposed by [8] by proposing a watermarking system thatembeds a watermark in the integer part of the selected DCTcoefficients and another one in the decimal part. This systemmakes use of the decimal part, rather than neglecting itwhich increases the payload of the system and gives it theLossless characteristic. Our method uses the integer part aswell but, does not neglect the decimal part. The decimal partis left intact.

This paper is organized as follows. In section II, we briefthe proposed technique, and give steps for both thewatermarking stage, and the extraction stage. Section IIIgives the analysis of the transforms used, and reports theexperimental results. Finally we conclude our work insection IV.

II. PROPOSED METHOD

Traditional watermarking techniques in the DCT domainwork on integers; they truncate or round the DCTcoefficients before embedding. This ignores the decimal partwhich in turn causes some image details to be lost. Othertechniques embed in both integer and decimal parts of thecoefficients. This preserves the details in the decimal part,but they are altered by embedding.

The proposed system takes this in consideration, andembeds only in the integer part of the coefficients, andpreserves the decimal part of the coefficients unaltered, bysplitting integer and decimal parts, and embedding in theinteger part only and then rejoin them together, which in turnminimizes the visual artifacts as much as possible.

Our method also increases the security of the watermarkby applying the Hadamard transform matrix to thewatermark prior to embedding. One of the properties of thistransform that encouraged using it is the fact that it is an

invertible matrix, and could be recursively computed, and itis computationally inexpensive.

A. Watermark EmbeddingEmbedding the watermark requires the following steps,

and results in an invisible watermark with no visual artifacts:1. The host image is acquired and transformed from RGB,

to HSI color space.2. Then it is transformed to the frequency domain, by

processing each 8 x 8 block independently.3. We embed the first watermark in the intensity

component of the HSI notation of the image.Embedding is done block wise in the transformedimage not pixel wise.

4. The watermarked component (intensity) is transformedback from the frequency domain.

5. Now, we embed the spatial watermark in the HSInotation of the cover image. The watermark is spreadagainst the three layers (H, S, and I), in differing bitplanes. Two groups of bit planes were used, (1, 2, and3) and (2, 3, and 4)

6. The watermarked image is post processed, and thentransformed back to RGB color space.

Fig. 1, abridges the former steps, and gives a generalframework for the embedding part of our proposed system.

B. Watermark ExtractionExtracting the watermark requires only the watermarked

Watermark lo Preprocessing I - ProcessedWatermark

Host image * PreprProcessed~~~~ ~~Host 1

Watermarked Post Processing Embeddingimage

part

Fig. 1. Embedding stage. This figure shows a block diagram of theembedding process. It also shows that there are two differentpreprocessing stages, one for the watermark, and the other for the host(cover) image, and one post processing stage for the result(watermarked image).

image (blind extraction), and any keys (if used atembedding) to be supplied to the extractor, which in turnextracts the watermark.

The general framework for the extraction process isshown in Fig. 2.

III. ANALYSIS AND EXPERIMENTAL RESULTS

The proposed method uses three main transforms appliedto both the watermark, and the cover image. First thewatermark is preprocessed with the Hadamard transformmatrix, represented in H, which can be obtained by the

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formula shown in (1). This equation, (1) represents aHadamard matrix of order 2J, where J is any natural

Watermarked 1 Preprocessing | Extractor|image LL

Extracted - Backward Processing Processed ExtractedWatermark Watermark

Fig. 2. Extraction stage. This figure shows a block diagram of theextraction process. It also shows that extracted watermark, is in aprocessed form, and that it needs to be further processed (backwardprocessing) before it is ready to be used.

number. The matrix of the second order is given in (2); it isused as a base for larger orders. The elements of thistransform take only two values; 1 and -1, hence suitable fordigital image processing.

HJJ HJ(H JJ= (1IHi -Hi

HH2J2J = I1 - 1

The Hadamard matrix is an invertible one. The inversewas recursively computed by using (3).

S =1-3

) [min(R, G, B)]Si(R+G+B)[i(GB]The intensity component was computed by using (6).

1I (R+G+B)

3

Before applying this transform, the RGB values must benormalized to the range [0, 1]; the resulting image is alsonormalized to this range for the testing phase [3].

Converting back from the HSI color space to RGB colorspace is done depending on the sector to which H is located.These sectors are of 120° intervals [3].

The method was tested on a wide range of images andwatermarks; a sample set of host images is shown in Fig.3,and some watermark images are displayed in Fig.4.Simulation results include the tests performed on thewatermarked images. The similarity results for the extractedwatermarks and the original ones are presented by the

) correlation measurement between the formerly mentionedwatermarks.

(2)

-1 1

The other two transforms DCT and HSI are applied to thecover image, they transform the image from the spatial to thefrequency domain, and from RGB to biological color model(HSI) respectively.

The DCT transform used, is the two dimensional DCT. Itis performed in a block wise manner of the image. Theinverse of this function is obtained by the Inverse DiscreteCosine Transform (IDCT).

The HSI transform, converts the image from RGB to HSIcolor space according to the following equations, we used(4) to compute the H component of each RGB pixel.

H= 0# if B<G

360-0 if B>G

With, 0 representing the angle measured with respect to thered axis of the HSI space. It was calculated by using (4.1)

co 2[(kR G)+(R B)] (4.1

(R -G)s + (R -BcG - B)wUsing (5), the saturation component was calculated.

Ja) tU)

Fig. 3. Sample test image, all of 256 x 256 pixels. (a) Girls; it isconsidered to be high density image. (b) Fish; it has a wide range ofcolors. (c) Plane, it is considered to be low density image.

(a) (b) (c)

Fig. 4. Sample watermarks, all of 128 x 128 pixels. (a) Biometricsignature. (b) Biometric fingerprint. (c) Logo.

Table I summarizes the results of the tests performed on

the Girls image shown in Fig. 3 (a), watermarked with thebiometric signature shown in Fig. 4 (a).

Images relative to test reported in Table I, are shown inFig. 5, they provide a visual support to realize the amount of

) attacks, and distortions applied to the watermarked images.Corresponding watermarks, spatially extracted are shown inFig. 6. In Fig. 7, we show the extracted watermarks from theDCT domain after the attacks.

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(5)

(6)

3)

TABLE ISIMULATION RESULTS OF THE GiRLs IMAGE

Correlation Correlation

Attack of extracted of extractedAttack ~~spatial DCT

watermark watermarkNormal 1 0.9962JPEG lossy Qa = 25 -0.0078 0.9962JPEG lossy Q = 50 -0.0106 0.9962JPEG lossy Q = 75 -0.0077 0.9962salt & pepper 0.05 0.7493 0.9962Gaussian noise 0.05 -0.0082 0.9962Rotate 90° 1 0.9962Rotate 180° 0.9985 0.9962Rotate 270° 1 0.9962Gaussian noise 0.05 + 0.0067 0.9962Rotate 90°

aQ: quality factor of the JPEG compression

X h; | N ' S ;N {N e . {~~~~~~~~~7, =AmO(d) (e) (f)

(g) (h) (i)

()

Fig. 6. Extracted watermarks Spatially from Fig. 5 (a)Normal test (No attack), (b) JPEG, Q = 25, (c) JPEG, Q =

50, (d) JPEG, Q = 75, (e) Salt & pepper 0.05, (f) Gaussiannoise 0.05, (g) Rotate 90°, (h) Rotate 180°, (i) Rotate 270°,(j) Complex attack of Rotate 90° and salt & pepper 0.05

(a) (b) (c)

(d) (e) (t)

(J)Fig. 5. Corresponding images of Table I. (a) Normal test (No attack),(b) JPEG, Q = 25, (c) JPEG, Q = 50, (d) JPEG, Q = 75, (e) Salt &pepper 0.05, (f) Gaussian noise 0.05, (g) Rotate 90°, (h) Rotate 180°,(i) Rotate 270°, (j) Complex attack of Rotate 90° and salt & pepper0.05

We demonstrate the results of applying the biometricsignature to the Fish image (see Table II). It presents theresults of extracting the watermarks after applying theattacks. Some complex attacks are applied; multiple attacksapplied consequently to the watermarked image beforeextraction.

(g) (h) (i)

()Fig. 7. Extracted watermarks from the DCT domain fromFig. 5 (a) Normal test (No attack), (b) JPEG, Q = 25, (c)JPEG, Q = 50, (d) JPEG, Q = 75, (e) Salt & pepper 0.05, (f)Gaussian noise 0.05, (g) Rotate 90°, (h) Rotate 180°, (i)Rotate 270°, (j) Complex attack of Rotate 90° and salt &pepper 0.05

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TABLE IISIMULATION RESULTS OF THE FISH IMAGE

Correlation Correlation

Attack of extracted of extractedAttack ~spatial DCT

watermark watermarkNormal 0.9995 1JPEG lossy Qa = 25 0.0057 1JPEG lossy Q = 50 0.0048 1JPEG lossy Q = 75 -0.0067 1salt & pepper 0.05 0.8082 1Gaussian noise 0.05 4.2300e-04 1Rotate 90° 0.9976 1Rotate 180° 0.9979 1Rotate 270° 0.9990 1Gaussian noise 0.05 + 0.0035 1Rotate 180° bSalt and pepper 0.05 -0.0059 1+Rotate 180° +JPEG 75 b

aQ: quality factor of the JPEG compressionbThese represent complex attacks applied consecutively to the

watermarked images

Table III lists the results of applying a logo watermark tothe plane image, and also provides some complex attacks,alongside with the normal attacks.

TABLE IIISIMULATION RESULTS OF THE PLANE IMAGE

Correlation Correlation

Attack of extracted of extractedAttack ~spatial DCT

watermark watermarkNormal 0.9995 0.9938JPEG lossy Q' = 25 -0.0306 0.9938JPEG lossy Q = 50 -0.0042 0.9938JPEG lossy Q = 75 -0.0067 0.9938salt & pepper 0.05 0.8064 0.9938Gaussian noise 0.05 -0.0085 0.9938Rotate 90° 0.9976 0.9938Rotate 180° 0.9979 0.9938Rotate 270° 0.9990 0.9938salt & pepper 0.05 + -0.0062 0.9938JPEG lossy Q' = 25 bSalt and pepper 0.05 0.8064 0.9938+Rotate g9o b

'Q: quality factor of the JPEG compressionbThese represent complex attacks applied consecutively to the

watermarked images

robustness against other geometric attacks, such as cropping,rescaling. Applying other transforms that the Hadamard, andimplementing the idea on other frequency domaintransforms, such as wavelet.

REFERENCES

[1] S. Mohanty, K.R. Ramakrishnan, and M. Kankanhalli, "A DCTdomain visible watermarking technique for images", (1998), Dept. ofComp. Science & Engg. University of South Florida, Dept. ofElectrical Engg. Indian Institute of Science Bangalore, School ofComputing National University of Singapore Kent Ridge.

[2] Sahoo T., Christian Collberg, (2004), "Software watermarking in thefrequency domain: Implementation, Analysis, and Attacks",Department of Computer Science, University of Arizona

[3] Gonzalez, Woods, and Eddins, "Digital Image Processing UsingMATLAB", Prentice Hall, 2004, pp. 203-208

[4] A. D. Marshall, (2003.10.13). "Dave's home page ". CardiffUniversity. Available h a

[5] A. Fabien, P. Petitcolas, J. R. Anderson, and M. G. Kuhn. "Attacks oncopyright marking systems". Second workshop on informationhiding, LNCS, Portland, Oregon, USA, April, 1998, vol. 1525.

[6] V. Darmstaedter, J. F. Delaigle., J.J. Quisquater, B. Macq, "Low costspatial watermarking". 1998, Laboratoire de Telecommunication etTeledetection Universite catholique de Louvain.

[7] S. Maity, M. Kundu, "Robust and Blind spatial watermarking indigital image" , 2001 ,Dept.of Electronics & TelecommB.E.College(D.U.), Machine Intelligence Unit Indian StaticalInstitute

[8] Al-Omari R., "Watermarking in content authentication andcopyright protection." Master Thesis, 2004, the University of Jordan.

[9] Abdel-Majeed L. R., "Digital watermarking System in the DCT andHadamard Domain for the proof of Ownership", CSIT2006,Amman-Jordan, April 5th - April 7th, 2006.

IV. CONCLUSION

In this paper, we proposed a novel method forwatermarking in the biological color space (HSI), and DCTdomain. It has proven its robustness against attacks,including the geometric attack of rotation. It has been shownthat this method adds no visual artifacts to the watermarkedimage, although the watermark size is relatively bigcompared to the host image, not forgetting that twowatermarks are embedded of the same size.

The future work is basically directed toward more

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