2012 International Conference on Communication, Information & Computing Technology (ICCICT), Oct. 19-20, Mumbai, India
A Semi-blind Image Watermarking based on Discrete Wavelet Transform and Secret Sharing B Surekha
Dr GN Swamy
Associate Professor, Department of ECE, TRR College of Engineering Hyderabad, INDIA.
[email protected]
Professor, Department of ECE, VR Siddhartha Engineering College, Vijayawada, INDIA.
[email protected]
Abstract — In this paper the concepts of frequency domain watermarking and Secret Sharing are combined to protect the copyrights of a digital image. The proposed method employs the concept of XOR-based Visual Secret Sharing (XVSS) to split a watermark into two unexpanded parts, a public watermark and a private watermark. The private watermark is extracted from the features of host image and original watermark. The public watermark can be extracted from the controversial image at any time without the need for original host image and/or watermark. Since private watermark is needed in recovering the original watermark, the proposed scheme comes under the category of semi-blind watermarking. The proposed watermarking technique aims at improving the security of similar watermarking schemes by processing LL sub-band coefficients of Discrete Wavelet Transform (DWT) of the host image to satisfy central limit theorem. The simulation results reveal that the proposed method can resist to a variety of common image processing manipulations. Keywords- Central Limit Theorem; Copyright Protection; Digital Watermarking; Discrete Wavelet Transform; Visual Secret Sharing
I.
INTRODUCTION
Due to rapid growth in computer and communication technologies, the transmission of multimedia data has become easy. Many multimedia agencies are now very much concerned about the data piracy. To address this issue, a variety of digital watermarking techniques have been developed. These techniques allow the owners to embed copyright information called watermarks into their multimedia data. These watermarks can later be extracted to identify the right owner. The important criteria to be satisfied by any watermarking technique are robustness, simplicity, imperceptibility, high capacity and security. Digital Image watermarking techniques can be roughly classified into two groups, namely the traditional and zero watermarking techniques. Traditional watermarking techniques [1-6] embed watermarks by directly modifying the pixels in spatial domain or by modifying their transformed coefficients. The zero watermarking techniques [7-21] conceal the watermarks without distorting the host image at all. This is achieved by adapting the concept of Visual Secret Sharing.
Visual Secret Sharing (VSS) [22] is a cryptographic technique designed to share digital images among n participants in such a way that any k (k ≤ n) participants can decode the secret image without the need for computational devices. In recent years, a two participant model of VSS is widely adapted in protecting the copyrights of high precision digital images. A two participant model of VSS encodes a secret binary image into two shares. Each share looks like a noisy binary image with equal number of black and white pixels. While creating the shares, each pixel in the original secret image is replaced with an array of 2×2 pixels. The two possible array combinations which are used here are shown in Fig. 1. A white (black) pixel is replaced with identical (complementary) arrays. VSS achieves ideal security when the probability of selecting either array combination, for either pixel color is same. Fig. 2 shows an example of the two participant model of VSS. Fig. 2(a) is the original secret image. Fig. 2(b) and 2(c) shows the share images produced from the original. These shares are xeroxed onto transparent sheets and are distributed to the participants. Fig. 2(d) is the recovered image, obtained after overlaying the share images one above the other. Note that, the recovered image is a low contrast version of the original one. This is due to substitution of array of pixels for each pixel in the original image.
Fig. 1 Array Combinations used in basic VSS scheme
(a)
(b)
(c)
(d)
Fig. 2 Example of a two participant model of VSS scheme (a) Secret image (b) Share1 (c) Share2 (d) Decoded image
978-1-4577-2078-9/12/$26.00©2011 IEEE
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2012 International Conference on Communication, Information & Computing Technology (ICCICT), Oct. 19-20, Mumbai, India Irrespective of the working domain, the working principle of zero watermarking techniques based on VSS involves two phases: the private watermark generation and registration, the public watermark generation and original watermark reconstruction. The private watermark is generated from a secret key, the original watermark and some features of the host image. The private watermark is secretly registered with a trusted third party who acts as an arbitrator. The public watermark can be extracted from the controversial image at any time without the need for original host image and/or original watermark. The private watermark and the public watermark can be combined to recover an undistorted watermark. Since private watermark is needed in extracting the watermark, the scheme is called semi-blind. In this paper, a new Discrete Wavelet Transform (DWT) domain zero watermarking technique, based on XOR VSS is proposed. It aims at improving the security of similar watermarking methods that selects LL sub-band coefficients of Discrete Wavelet Transform (DWT) as the unique features. The simulation results reveal that the proposed method can resist to a variety of common image processing manipulations. The proposed method also results in unexpanded private and public watermarks, to result a high quality extracted watermark. The rest of the paper is organized as follows. Section 2 briefly reviews the related works. Section 3 describes the proposed private and public watermark generation and verification phases. Experimental results and comparisons are given in Section 4. Finally, Section 5 concludes the paper. II.
LITERATURE REVEIW
This section will briefly review the DWT domain zero watermarking techniques based on VSS. Most of these watermarking techniques fail by not meeting the security requirements of either VSS or watermarking. The security of any watermarking technique fails, if it leads to high probability of false positives. A false positive is a result of extraction of a watermark from an unauthorized image, which doesn’t actually belong to the owner. Since, false positives encourage malicious owners in claiming other unauthorized images, this problem should be avoided. This problem pronounces if the selected feature vector is not unique. Lou et al., [16] proposed an LTL scheme which constructs a secret binary matrix by comparing the modified Discrete Wavelet Transform (DWT) coefficients obtained, from two selected sub bands of same level with that of LL sub bands coefficients. The security of this scheme is analyzed by Chen et al, [19] and proved that the LTL scheme increases the probability of false alarm and leads to ambiguity in copyright verification. To overcome this drawback, Park et al [17] used a different threshold for comparison. Though this scheme reduces the probability of false alarm to some extent, it fails in secure verification of watermark. The security of Park’s scheme is analyzed by Xing et al in [18] and proved that, the scheme becomes independent of the host image and the secret key. This problem arises due to majority of black sub pixels in their array combinations.
978-1-4577-2078-9/12/$26.00©2011 IEEE
In this paper, we propose a watermark hiding scheme that reduces the probability of false alarm by adapting the concepts of sample averages and central limit theorem while extracting the image features. III.
THE PROPOSED WATERMARKING PROCESS
The proposed watermarking process doesn’t physically embed the watermarks into the host image. Instead, the process hides the watermark in two random images called private watermark and public watermark. The process of generating these images is similar to generating the share images in two participant model of XOR-based VSS except for the following differences: 1. Instead of generating both the shares at a time, one share (private watermark) is generated during watermark hiding phase and the other share (public watermark) is generated during watermark verification phase. 2. In addition to using a random key for selection of array combinations, the features extracted from the host image are also used. The copyright protection with the proposed method involves two steps: 1. Watermark hiding phase which involves private watermark generation and its registration. 2. Watermark extraction phase which involves public watermark generation and copyright verification. A.
Watermark Hiding Phase
Before publishing the host image, a private watermark which is of size equal to the original watermark is generated by processing the LL sub-band coefficients of the host image as shown in Fig. 3. The host image H is first decomposed into two DWT levels. If the original watermark consists of P pixels, then the hiding algorithm randomly chooses P pixel positions from LL2 sub-band. For this purpose a secret key K is used as a seed. An averaging mask of size 7×7 is centred at every pixel position Pi to obtain a feature matrix M. A binary matrix B is now constructed by comparing every element of feature matrix with some threshold T. The threshold T is simply the average of all the elements in feature matrix M. A private watermark image is now constructed using the rules given in Table 1. The private watermark is then time-stamped and is confidentially registered with a trusted third party. TABLE 1 CONSTRUCTION RULES OF XOR-BASED VSS Watermark Pixel Element in matrix B
White 0
1
Black 0
1
Private Watermark Pixel
Public Watermark Pixel Private Watermark Public Watermark
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2012 International Conference on Communication, Information & Computing Technology (ICCICT), Oct. 19-20, Mumbai, India B.
Host Image
Key Feature Matrix Average
Original watermark
Comparator XVSS encoding rules
Private watermark
Fig. 3 Proposed Watermark hiding phase: Private watermark generation
Claimed Image
Watermark Extraction Phase
The claimed image H’ is first decomposed into two DWT levels. The secret key K is used as a seed to randomly select P pixel positions from LL’2 sub-band. An averaging mask of size 7×7 is centred at every pixel position Pi to obtain a feature matrix M’. A binary matrix B’ of size equal to the original watermark is now constructed by comparing every element of feature matrix with some threshold T’. The threshold T’ is the average of all the elements in feature matrix M’. A public watermark is now constructed using the rules given in Table 1. A bitwise XOR operation is then performed on private and public watermarks to reconstruct the original watermark. The process of public watermark generation and original watermark verification is shown in Fig. 4. Note that the size of original, extracted and private/public watermarks are exactly same. It is the XOR-based Visual Secret Sharing (XVSS) that helps in generating unexpanded versions of watermarks. It indirectly improves the quality of extracted watermark. The proposed scheme also improves the security of watermarking by selecting sample averages of LL sub-band coefficients and a different threshold (so as to satisfy the central limit theorem) when compared to similar watermarking schemes. IV.
SIMULATION RESULTS
To demonstrate the performance of the proposed scheme, the proposed watermarking is performed on a gray level benchmark image (Baboon) of size 512×512 pixels. It is shown in Fig. 5(a). A binary watermark of size 50×150 shown in Fig. 5(b) is hidden into the Baboon image by splitting it into private and public watermarks. They are shown in Fig. 5(c) and 5(d). The recovered watermark from an unaltered host image is shown in Fig. 5(e). Note that, the size of the recovered watermark is same as the original watermark. Also the quality of extracted watermark is good without any contrast loss.
Key Feature Matrix (a) Average
Comparator XVSS encoding rules Public watermark
(b)
(c)
(d)
(e)
XOR Private watermark Extracted watermark Fig. 4 Proposed Watermark extraction phase: Public watermark generation and copyright verification.
978-1-4577-2078-9/12/$26.00©2011 IEEE
Fig. 5 Results of proposed watermarking scheme (a) Host image (b) Original watermark (c) Private watermark d) Public watermark (e) Reconstructed watermark
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2012 International Conference on Communication, Information & Computing Technology (ICCICT), Oct. 19-20, Mumbai, India Several experiments are then performed to test the robustness of the proposed scheme against common image processing attacks. The Baboon image is subjected to several attacks using MATLAB Image Processing Toolbox. In addition to observing the subjective quality of extracted watermarks a quantitative measurement namely, Normalized Correlation (NC) is also calculated to measure the similarity between the original and extracted watermark. If w×h is the size of the watermark, then NC is expressed as: w
NC =
h
∑∑ ( X
i, j
⊕ X 'i, j )
i =1 j =1
w× h
(1)
Where Xi,j corresponds to pixels of original watermark and X’i,j corresponds to pixels of extracted watermark. To measure the similarity between the original and attacked images a quantitative measurement namely, Peak Signal to Noise Ratio (PNSR) is defined in terms of Mean Square Error (MSE) as follows:
255 2 PSNR = 10 × log MSE MSE =
r
(2)
(3)
Where Hi,j denotes pixels of original host image and H’i,j denotes pixels of attacked watermarked image, and r × c denotes the image size. Table 2 lists the performed attacks along with the corresponding PSNR and NC values. The lossy JPEG compression is very common while storing or transmitting any image. An intentional attack of this type is performed by compressing the image with quality factor 10. It can be seen from Table 2 that the corresponding NC value is 0.9813. The blurring, sharpening and median filtering of the images are very commonly used methods to improve their subjective quality. Attacks of this type are performed with a window size 3×3. A noise added image is obtained by adding 20% salt and pepper noise to the host image. The scaling of an image is done by first reducing the original host image size from 512×512 pixels to 256×256 pixels, and then zoomed to its original size by means of pixel replication. The cropped image is obtained by cropping 25% of the original host image. To test the robustness against rotation attack the original host image is rotated 10o in counter clock wise direction. From the results in Table 2 it is clear that the proposed scheme results in most NC values closer to 1, indicating satisfactory robustness for the given attacks. The effectiveness comparison of the proposed scheme with some similar VSS-based watermarking schemes in the literature is given in Table 3. The comparison is mainly focused on the following properties: pixel expansion, extracted watermark quality and the probability of false positives or indirectly security. Note that the scheme is ideal if there is no pixel expansion, no contrast loss and if the probability of false
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TABLE 2 SIMULATION RESULTS OF PROPOSED WATERMARKING SCHEME
Baboon PSNR (dB) 30.42 29.12 28.29 27.57 31.69 34.12 30.99 28.69 36.11
Attacks JPEG (QF=10%) Blurring (3×3) Sharpening (3×3) Histogram Equalization Median Filter (3×3) Salt & Pepper Noise Scaling (1/2) Rotation (3o right) Cropping (10%)
NC 0.9813 0.9426 0.9750 0.9841 0.9885 0.9380 0.9757 0.8489 0.8545
TABLE 3 COMPARISON OF VARIOUS VSS BASED WATERMARKING SCHEMES
Criteria
c
1 ∑∑ ( H i , j − H 'i , j )2 r × c i =1 j =1
positives is less. From the results in Table 3, it is clear that only the proposed scheme satisfies all the criteria mentioned above.
Scheme Lou, Tso and Liu[16] Park, Yoon and Yoo[17] Xing and He[18] Proposed Scheme
Pixel Expansion
Contrast loss Yes
Prob. of false positives Very high
2
No
No
No
Low
No
2
Yes
High
Yes
No
No
Very low
High
V.
Security
CONCLUSIONS
The concept of XOR-based Visual Secret Sharing (VSS) is used to hide a digital watermark into Discrete Wavelet Transform of a host image. The features of the image are used to split the watermark into two random binary share images called private and public watermarks. One image is generated during watermark embedding phase and is kept secret with an arbitrator. The other share is extracted from the controversial image during watermark extraction phase. Both the images are combined to extract the original watermark. Unlike, the existing schemes, the proposed scheme don’t expand the shares. It also results in high quality extracted watermarks. The proposed method of watermark hiding utilizes sample averages and central limit theorem to improve the security of existing techniques.The simulation results reveal that the proposed scheme has satisfactory robustness to several image processing attacks. REFERENCES [1] N. Nikolaidis and I. Pitas, “Robust image watermarking in the spatial domain,” Signal Processing, vol. 66, pp.385–403, 1998. [2] R.G. Van Schyndel, A.Z. Tirkel and C.F. Osborne, “A digital watermark,” Proc. of IEEE International Conference on Image Processing, 1994, pp. 86–90. [3] C.T. Hsu and J.L.Wu, “Hidden digital watermarks in images,” IEEE Transactions on Image Processing, vol.8, pp. 58–68, 1999.
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2012 International Conference on Communication, Information & Computing Technology (ICCICT), Oct. 19-20, Mumbai, India [4] G.C. Langelaar and R.L. Lagendijk, “Optimal differential energy watermarking of DCT encoded images and video,” IEEE Transactions on Image Processing, vol. 10, pp. 148–158, 2001. [5] S.H. Wang and Y.P. Lin, “Wavelet tree quantization for copyright protection watermarking,” IEEE Transactions on Image Processing, vol. 13, no. 2, pp. 154–165, 2004.. [6] M. Barni, F. Bartolini and A. Piva, “Improved wavelet-based watermarking through pixel-wise masking,” IEEE Transactions on Image Processing, vol. 8, pp. 783–791, 2001. [7] J. Tian, “Reversible data embedding using a difference expansion,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, pp. 890–896, 2003. [8] C. De Vleeschouwer, J.F. Delaigle and B. Macq, “Circular interpretation of bijective transformations in lossless watermarking for media asset management,” IEEE Transactions on Multimedia, vol. 5, pp. 97–105, 2003. [9] M.U. Celik, G. Sharma, A.M. Tekalp, E. Saber, “Lossless generalizedLSB data embedding,” IEEE Transactions on Image Processing, vol. 14, pp.253–266, 2005. [10] C.S. Hsu and S.F. Tu, “Digital Watermarking Scheme with Visual Cryptography”, in Proc. of The Int. Multi Conf. of Engineers and Computer Scientists, Hong Kong, China, 2008., pp. 659-66, [11] S-F Tu, and C-S Hsu, “Digital Watermarking Method Based on Image Size Invariant Visual Cryptographic Scheme”, in IEEE Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, 2009, pp.362-366. [12] Nagaraj V. Dharwadkar and B.B.Amberker, “Watermarking Scheme for Color Images using Wavelet Transform based Texture Properties and Secret Sharing”, Int. Journal of Signal Processing, vol.6, no.2, pp. 93100, 2010. [13] Hwang, R., “A Digital Image Copyright Protection Scheme based on Visual Cryptography,” Tamkang Journal of science and Engineering, vol.3, no.2, pp. 97 - 106, 2002.
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[14] C-C. Chang and J-C. Chuang, “An image intellectual property protection scheme for gray-level images using visual secret sharing Strategy,” Pattern Recognition Letters, vol. 23, no. 8, pp.931-941, 2002. [15] M Hassan A, and M Khalili A, “Self Watermarking based on Visual Cryptography,” in proc. of World Academy of Science, Engineering and Technology, Oct 2005, vol. 8, pp. 159-162. [16] D.C. Lou, H.K. Tso, and J.L. Liu, “A copyright protection scheme for digital images using visual cryptography technique,” Computer Standards and Interfaces, vol.29, no.1, pp.125-131, 2007. [17] G.D.Park, EI. Yoon, and KY Yoo, “A new copyright protection scheme with visual cryptography,” in Proc. of the Second Int. Conf. on Future Generation Communication and Networking Symposia, 2008, pp. 6063. [18] Y Xing, and JH He, “A new robust copyright protection scheme for digital images based on visual cryptography,” in Proc. of the 2010 Int. Conf. on Wavelet Analysis and Pattern recognition, Qingdao, 11-14 July 2010, pp.6-11. [19] Chen T.H., Chang C.C., Wu C.S. and Lou D.C, “On the security of a copyright protection scheme based on visual cryptography,” Computer Standards & Interfaces, vol. 31, no.1, pp. 1-5, 2009. [20] Shang-Lin Hsieh, Lung-Yao Hsu, and I-Ju Tsai, “A Copyright Protection Scheme for Color Images using Secret Sharing and Wavelet Transform,” World Academy of Science, Engineering and Technology, vol. 10,pp.17-23, 2005. [21] Shang-Lin Hsieh and I-Ju Tsai, “A Copyright Protection Scheme for Satellite Images Using Secret Sharing and Wavelet Transform,” in Proc. of the IEEE International Conference on Systems, Man, and Cybernetics, October 8-11, Taipei, Taiwan, pp.501-506, 2006. [22] M. Naor and A. Shamir, “Visual Cryptography,” in Proceedings of Advances in Cryptology：Eurpocrypt＇94, vol. 950, Springer, Berlin, pp. 1-12, 1995.
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