Multipurpose Color Image Watermarking Algorithm Based ... - wseas.us

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Multipurpose Color Image Watermarking Algorithm Based on IWT and Halftoning C. SANTIAGO-AVILA, M. GONZALEZ LEE, M. NAKANO-MIYATAKE, H. PEREZ-MEANA Sección de Posgrado e Investigación, Esime Culhuacan Instituto Politecnico Nacional Santa ana # 100 MÉXICO CITY [email protected], [email protected] Abstract: - In the security of digital contents, almost all previous works tried to attend either the copyright protection issue or the content authentication issue, however recently some proposals try to solve simultaneously both problems. In this paper, a multipurpose method that tries to solve both problems for color images, using two watermarking algorithms, is proposed. The first algorithm is based on a self-embedding technique which uses the halftone version from the Y, Cr and Cb channels of the original color image as the watermark, then, the Quantization Index Modulation (QIM) method is used to embed in the integer Wavelet transform (IWT) domain. In the second algorithm, the halftone watermark image generated from luminance channel Y is watermarked manipulating their flipabble pixels to embed a bits sequence related to the owner’s copyright information.

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This paper shows a novel multipurpose watermarking algorithm to embed two different kinds of watermarks into the color image. The first watermark sequence is a halftone version generated from three color channels (Y, Cb and Cr) of the original color image using the Floyd-Steinberg error diffusion method [4]. Then each halftone image is embedded into each corresponded color channel using Quantization Index Modulation (QIM) method [5] in the Integer Wavelet Transform (IWT) domain. These watermark sequences are used for content authentication purpose. Before the watermark embedding stage in the IWT domain, the halftone image from luminance channel Y is modified to embed a binary watermark sequence related to copyright information using watermarking technique proposed in [6]. This watermark is used for copyright protection. The intentional and unintentional attacks were carried out to evaluate the watermark robustness and the detection capability of altered regions. The experimental results have shown a good performance for both purposes: copyright protection and contents authentication. The remainder of this paper is organized as follows. In section 2, the proposed scheme is described and an evaluation results are shown in section 3. Finally some conclusions are remarked.

Introduction

Nowadays the great popularity of the internet has become easy the exchange of lots of digital files, but the most of these files can be easily modified without any trace. Due to these situations, many schemes based on watermarking technique have been developed to solve either the copyright protection problem or the contents authentication problem. However usually these two problems are happened simultaneously, therefore an efficient multipurpose algorithm to solve at same time the both problems: copyright protection and contents authentication, will be required. In the literature, some multipurpose watermarking algorithms have been proposed. The algorithm proposed by Fan Gu et.al [1] uses sub-sampling to embed two robust watermarks, then, DCT domain is used to exploit the human visual System (HVS) feature. Under unintentional attacks, the watermarks survive even under JPEG compression and its integrity is measure by Normalized Hamming Similarity (NHS) but the intentional attacks, such as contents alteration, are not considered. In [2], ZheMing Lu et al. proposed a novel multipurpose algorithm based on the multistage vector quantizer structure to embed a semi-fragile watermark and robust watermark in different stages. Both watermarks can be extracted without the original image. The principal disadvantage is that the method uses six keys in the extraction process, two of them have to be generated from the well-know iterative clustering algorithm [3] that is often referred to as the generalized Lloyd algorithm (GLA).

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2. Quantization Index Modulation (QIM) Algorithm QIM algorithm is used to embed the watermark sequence in section 3.1. A binary image is divided into small blocks and a Quantization Step is defined

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(size and Qs is explained in the following section). The number of pixels per block, is the feature used by QIM. To embed a “0” in a block, some pixels are changed so that the total number of black pixels in that block has to be 2kQs for some integer k, and has to be (2k+1) Qs to embed a “1”. A larger Q gives higher tolerance to noise at the expense of decreased image quality.

3.1 Watermarking for Copyright protection In [6], a watermarking algorithm for binary images, including document images, is proposed. This algorithm measures the smoothness and the connectivity of each binary pixel to determine the flippable pixels that can be flipped (from back to white and vice versa) without causing any distortion to the binary image. This algorithm is applied to the halftone image generated from only luminance channel Y to embed watermark sequence for copyright protection purpose. Once the flippable pixels are found, the halftone image is divided into blocks of NxN pixels and one bit of the watermark sequence is embedded into each block, using QIM algorithm. Fig. 1 (a) shows flippable pixels and (b) shows halftone image divided into blocks of NxN pixels, where N is computed by watermark bits length LxL.

The above approaches can be characterized more generally by

(1) where vi is the ith original feature, v’ is the feature value after embedding, bi is the bit to be embedded in ith feature, and T( )is a prescribed mapping from feature values to hidden data values {0,1}. Detection is done by checking the enforced relationship: (2) where v’’i is the feature extracted from the ith block of a test image, and b’i is the estimated value of the embedded bit in the ith block.

(a)

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Fig. 1 (a) “Flippable” pixels, (b) Halftoned image divided in blocks.

Proposed Algorithm

In the proposed algorithm, two watermark sequences are embedded for two purposes: copyright protection and content authentication. The proposed watermarking algorithm is operated in YCrCb color space, therefore the color images with RGB color space firstly must be converted into YCrCb color space. The watermark sequence for content authentication is generated from each color channel (Y, Cr, Cb) using the Floyd-Steinberg error diffusion method [4] to convert into a binary halftone image. The binary halftone image generated from luminance Y channel is modified its flippables pixels using the method reported by [6] for copyright protection purpose. The halftone image of each color channel is embedded in the Integer Wavelet Transform (IWT) domain, because IWT offers better spatial-frequency property than DCT and unlike DWT, lossless forward and inverse transform can be performed. Using IWT, each color channel is decomposed into four subbands with integer elements (LL, LH, HL and HH). The sub-band LL of each color channel is chosen to embed the corresponded watermark sequence. As the watermarking algorithm, QIM method is used [5], which was described in the previous section.

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(b)

The watermark bit length (LxL) influences directly to the watermark robustness, therefore to obtain an adequate watermark length, the relationship between L and maximum quantification step size is analyzed. Figure 2 shows this relationship. If L is large (i.e 32), the robustness must be sacrificed, on the other hand, if L is small, the method becomes more robust, but the watermark length must be sacrificed. In the proposed algorithm, L=8 is selected as optimal length from robustness point of view. Then the block size N is calculated by N=L/M, where M is width and height of the image.

Fig. 2. Relationship between watermark length(LxL) and Maximum quantification step.

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The watermark is then 64 (8x8) bits sequence, which can be pseudorandom sequence generated by owner’s secret key or eight letters related to owner’s name, for example ASCII codes of eight letters “SEPI-IPN”, shown by Fig. 3.

authentication purpose. In Fig. 5, the general block diagram of the both watermarking schemes is shown. Firstly, the color image must be YCbCr color space, otherwise the color space (for example RGB) must be converted in YCbCr color space. Then each color channel Y, Cb and Cr of a color image is decomposed by IWT. Because the sub-band obtained by the decomposition is the half size of the original image in its width and height, the watermark sequence size must be reduced using down-sampling. For example, if the original image size is 512 x 512, the watermark sequence must be 256 x 256. LL subband is chosen to embed the watermark sequence; here QIM algorithm is also employed. As quantification step, Qs=9 is used, this value is the max possible value for Qs without causing distortion to the watermarked image. Finally Inverse IWT is applied to the four sub-bands to obtain the watermarked image.

S E P I E S I M E

Fig. 3. Watermark sequence for copyright purpose In Fig. 4, the original halftone image (a) and the watermarked one with 64 bits sequence (b) are shown.

3.3 Authentication Process

(a)

In the authentication process, three color channels (Y, Cr and Cb) of the watermarked and possibly altered color image is decomposed to four sub-bands using IWT, and from LL sub-band of each color channel, the watermark sequence for corresponded color channel is extracted by QIM extraction algorithm. The extracted watermark sequences are binary halftone images with possible distortion, which are converted in color image using wavelet-based inverse halftoning method proposed by [7]. The difference image Fig. 6 (k) is obtained between the watermarked image and the reconstructed image from extracted

(b)

Fig. 4 Binary halftone image and its watermarked version

3.2 Watermarking for Content Authentication Once each watermark sequence were generated from Y, Cb, and Cr channels using the Floyd-Steinberg error diffusion method and the watermark of luminance channel Y was modified for copyright purpose as shown in the previous section, the three binary watermark sequences are embedded into its corresponded color channel (Y, Cb, Cr) for content

Color Image

R

Y

G

Cb

B

Cr

HTY Halftoning (Floyd)

Logo LxL

Watermarking for Copyright Purpose

Key 1

HTCb HTCr

HTYw

IWT

Watermarking for content purpose (QIM)

Pseudoramndom Permutation

Key 2

Marked Color Image

IIWT

Fig. 5 General Block Diagram

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(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

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(j) (k) (l) Fig. 6 Evaluation results from watermark imperceptibility and tamper detection points of view.

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halftone images. This image is subdivided in blocks of 16 x 16 pixels, if the sum of the block is greater than Th=5000 these pixels are determined as altered pixels, otherwise they are authentic.

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When pseudo-random sequence generated by owner’s secret key is used as the watermark sequence, the watermark is sufficiently robust after the watermarked image is suffered some alteration shown by Fig. 6 (i), because in Fig. 7, when approximately 10% of pixels are altered, the BER of the extracted watermark is 0.0625, it is sufficiently small. If owner’s logotype is used as watermark sequence, shown by Fig. 3, one bit of 64 bits is changed (BER=aprox. 0.016), one letter is not extracted correctly. Therefore depending on application, the watermark sequence for copyright protection must be selected adequately.

Evaluation Results

The proposed multipurpose algorithm is evaluated from several points of view: watermark imperceptibility, tamper detection capability and watermark robustness. Figure 6 (a),(b) and (c) show Y, Cb and Cr channels, respectively of the original image, and (d), (e) and (f) are halftone images of (a), (b) and (c). Fig. 6(g) is original color image and (h) is the watermarked image with two watermarks (copyright protection and authentication purposes). Here PSNR of the watermarked image respect to its original one is 30.55dB. Although this value is not so good, the difference of both images (Fig. 6(g) and (h)) is not perceptible. Fig. 6 (i) is the altered image adding a flower and (j) is a recovered version of (i). Fig. 6(k) is the difference image between (i) and (j), and (l) is shown the detected altered region. From these results, the proposed algorithm can detect correctly the altered region.

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Conclusions

The multipurpose watermarking algorithm for color image is proposed, in which two types of watermark are embedded. The first watermark is for copyright protection using a binary sequence such as owner’s logotype or pseudorandom sequence generated by owner’s secret key as watermark. This watermark is embedded using flippable pixels of the halftone image generate from luminance channel Y of the color image. The halfone versions from all color channels are the second watermark sequences. The halftone image of each color channel is embedded into LL sub-band of IWT coefficients of respective color channel. Using two watermark sequences, the proposed scheme detect correctly the altered region of the image, when the watermarked image was suffered some alteration, and at same time owner can claim his ownership over the color image.

0,07 0,06 0,05 0,04

BER

0,03 0,02 0,01

References [1] F. Gu, Z. Ming, J. Pan Multipurpose Image Watermarkingin DCT Domain using Subsampling. Dept. of Autom. & Test, Harbin Inst. of Technol., China. Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on. , 23-26 May 2005, pp 4417 4420 Vol. 5 ,

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Fig. 7 Relationship between percentage of altered pixels and BER of the extracted watermark sequence.

The watermark sequence for copyright protection is extracted from the extracted halftone image of Y channel, using QIM extraction algorithm. The bit error rate (BER) of the extracted watermark sequence is measured when some pixels of the watermarked image is altered. Fig. 7 shows a relationship between percentages of the altered pixels of the image given by (3) and BER of the extracted watermark bits. Alterration % 

number of altered pixels

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[2] Z. Ming, D. Guo, S. Sun. Multipurpose Image Watermarking Algorithm Base on Multistage Vector Quantization. Department of Automatic Test and Control, Harbin Institute of Technology, Harbin 150001, China. IEEE Trans Image Process. 2005 Jun 14, pp 822-31. [3] Y. Linde, A. Buzo, and R. M. Gray, “An algorithm for vector quantizerdesign,” IEEE Trans. Commun., vol. 28, no. 1, pp. 84–95, Jan. 1980.

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[4] N. Venkata, B. Evans, “Adaptive Threshold Modulation for Error Diffusion Halftoning”, IEEE Trans. on Image Processing, 10(1), pp. 104-116, 2001. [5] B. Chen, G. W. Wornell, “Quantization index modulation: A class of provably good methods for digital watermarking and information embedding”, IEEE Trans. on Information Theory, vol. 47, no. 4, pp. 1423-1443, 2001. [6] M. Wu, N. Liu. Data hiding in binary images for authentication and annotation. IEEE Trans. on Multimedia, Aug. 2004, Fig. 16 (page 536) [7] R. Neelamani, R. Nowak, R. Baraniuk, “Modelbased inverse halftoning with wavelet-vaguelette deconvolution”, in: Proceeddings of international Conference on Image Processing, vol. 3, 2000, pp. 973-976.

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