Digital Watermarking for Forgery Detection in Printed Materials

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1 Lecture Notes in Computer Science 1 Digital Watermarking for Forgery Detection in Printed Materials Y.J.Song, R.Z.Liu, T.N.Tan National Lab of Pattern Recognition Institute of Automation, Chinese Academy of Sciences P.O.Box 2728 Beijing, , P.R.China {yjsong,liurz,tnt}@nlpr.ia.ac.cn Abstract. Forgery prevention and detection are of great social importance.this paper attempts to apply digital watermarking into forgery prevention.to embed a watermark,the wavelet transformation is first applied to the original image and the corresponding approximation image and detail images are obtained.the digital watermark is embedded into the most important DCT coefficients of the approximation image except the DC coefficient of the detail image through linearly additive operation.the corresponding watermark is extracted throught threshold judgement and the threshold is determined through the difference of two cycle print&scan and one cyle print&scan of the images.to improve the robustness of the orgorithm,the simple and effective repetition is applied to watermark configuration.and the CIE Lab color space is chosen to guarantee the repetition of the results and minimize the error brought by the transference of images between differnt equipments.experimental results show that the proposed algorithm can satisfy the requirements of forgery prevention for ordinary images,that is to say the digital watermark is robust to one cycle print&scan and fragile to two cycle print&scan. Compared with other forgery prevention and detection techniques,the algorithm described in this paper reduced the computation cost considerably as no other special material or equipment is required and ordinary user can verify the authentication of printing materials. This algorithm can also be used in printing materials copyright protection,such as the owner verification in certificates,passports,ect. 1 Introduction The increasingly networked society calls for effective measures for copyright protection, image authentication, etc. Digital watermarking thus comes into being and promotes the progress of the field. But we should not neglect those images largely in the form of presswork (trademarks, pictures, certification, ID cards, paper currency, passports, etc). For recent years, many people have been engaged in forgery of printed materials for illegal economic profit. The identical printing process brings the fact This work is supported by the Chinese NSF (Grant No ) and the Chinese Academy of Sciences.

2 Lecture Notes in Computer Science 2 fact that it is easy for a forger to make illegal copies of the original. Just take the passports as an example, from the China Police Department statistics, there are about 3 million false passports all over the world. And a comparative portion is absolutely counterfeited. The strike on counterfeit has never been stopped. People have thought of many different forgery prevention methods on color printing, such as laser forgery preventing, telephone code forgery preventing, computer network counterfeit preventing, etc. All these forgery-prevention techniques have worked on a certain degree, but the cost has increased greatly. People are looking forward to more costeffective schemes. In this paper, we attempt to apply digital watermarking into the forgery prevention field. The paper is organized as follows. Section 2 introduces the recent progresses of watermarking in printing systems. Section 3 puts forward the implementation scheme. Section 4 outlines the experimental results. And Section 5 makes the conclusions and presents the work to be continued. 2 Recent Progresses of Watermarking in Printing Recent public literatures show that some researchers have tried to apply watermarking into printing system. The watermarking scheme invented in Digimarc Company has been integrated in the most popular image processing tool-photoshop. The embedded watermark can survive printing and scanning on some degree. But the amount of watermark is very limited and the content of watermark is restricted in Digimarc ID, Distributor ID, Copyright Year, etc. Also it is sensitive to geometric transform. Pun [1] has devised a watermarking algorithm robust to printing and scanning. The PhotoCheck software developed in AlpVision Company by Kutter [2] is mainly focused on authentication detection of passports. As a passport belongs to the owner with his photo, this belongs to a content-based watermarking technique. When the photo is changed, the image with the watermark is of course lost and this just requires that the watermark hidden in the owner s passport is robust to one cycle of print and scan. Considering the special characteristic of FFT on rotation, scaling and cropping, Lin [3][4] has carried out the research on fragile watermarking rather early and obtained many useful conclusions on the distortion brought by print and scan. Researchers in China [5] began to hide some information in printing materials, using the function offered by PhotoShop. All these are focused on the watermark robust to one cycle of print and scan. For real forgery prevention, there are some other requirements as discussed in the following. Figure 1 and 2 illustrate watermark embedding and extraction processes both for a copyrighted product and a forged one. From the figures, we can see that the difference between the copyrighted and the forged is the process before watermark extraction. The copyrighted only needs one scan, while the forged requires more than one cycle of print and scan. It will be ideal if the watermark is robust only to the first cycle of print&scan, but fragile to the second cycle of print&scan.

3 Lecture Notes in Computer Science 3 Fig. 1. Embedding Process Fig. 2. Extracting Process

4 Lecture Notes in Computer Science 4 3 Implementation Method 3.1 Print&scan Distortion Analysis All the distortion in the print and scan process can be categorized into two types[3].the first type is distortion visible to human eyes, including changes of brightness and contrast, gamma correction, image halftone,dot diffusion, edge noise, etc. The printing of an image is from digital to analogous. Meanwhile, the resolution of a photocomposer is a key factor, which controls the fine degree of the halftone grids. On the contrary, the scanning is to convert an analogy image to its digital form. The resolution of a scanner is also an important factor. As with the increase of the resolution of the scanner, the inserting values are also increasing and the computing speed is decreasing. Considering all these factors, we choose 300dpi for printing and 600dpi~1200dpi for scanning in our experiments.the second type is geometric distortion invisible to human eyes,including rotation, scaling, cropping, etc.this distortion always occurs when locating the corresponding portion in the printing sheet with the original digital images. Some rotation is needed, as a sheet may not be very horizontal when it is put on the surface of a scanner. Numerous experiments show the rotation angle is at about 0.5 ~ 0.5. A certain cropping is necessary to cut the margins. And scaling is always indispensable, as the printing resolution and the scanning resolution are always inconsistent. There is still one point which is always neglected,that is the color conversions during print and scan.one image has different color space descriptions on different equipment. For example, it may be displayed in RGB space in computer, be edited in HSI space and be converted into CMYK space when it is published. Different color spaces have different gamut. So some information may be lost when converting between different spaces. It is important to select an appropriate color space among so many color spaces, including RGB space, CMY space, HIS(HLS, HSB)space YUV space, YIQ space, and YCrCb space and those based on CIE,including CIExyY space, CIELab space and CIELu*v* space. Meanwhile the CIELab space is recently the only one to describe color most exactly and independent of the equipment. So CIE Lab space is chosen. 3.2 Watermark Embedding and Extraction Methods The original image (ordinarily in the RGB mode) is first changed into CIELab mode, and the L portion is chosen to carry the watermark. The watermark This belongs to NLPR is taken as an example (the length of the watermark is defined as l). Firstly, each bit of the watermark is extracted and a sequence composed of 0 and 1 is obtained. 0 is changed to 1, 1 remains unchanged. The above sequence is repeated m times and the size of the total sequence is 8l*m. Secondly, a two-level multiresolution representation of the original image is obtained using a Haar wavelet trans-

5 Lecture Notes in Computer Science 5 form.the DCT transform is applied to the approximation image, the 8l*m largest coefficients are selected and the watermark is added with a linear additive function, just as Cox s method [6]. The strength of the watermark is controlled by a. Lastly, the inverse DCT of the above sequence is made,the corresponding inverse wavelet tranform is done to get the watermarked image which can be printed later. It is time to distinguish the copyrighted products and the forged ones. Firstly, one of the presswork is scanned and a scanned image with some margin is obtained (The sheet should better be put as horizontal as possible.). Secondly, the corresponding area with the original digital image is located. Thirdly a sequence W_j (i) is computed using the minus operation with the embedding process. M is chosen as a threshold, if the current value of W_j (i) is greater than M, then W_jj (i) is set to 1,otherwise is set to 0. If the number of 1s is greater than that of 0s in a bit of a character, then the bit is considered as 1s,otherwise 0.By repeating the above operation for all other bits, the watermark is extracted. At the same time, the bit-error rate curve can be obtained. If the whole eight bits of a character can be extracted (or the bit error rate of each bit of a character is less than 50%), then the extracted character is considered as correct. If all the characters can be extracted from the first cycle of the print&scan image, the watermark is considered robust to the first cycle of print&scan. If all the characters can not be extracted from the second cycle of the print&scan image, the watermark is defined fragile to second cycle of print&scan. Thus the watermark can claim the owner of the copyright and detect the forgery images. Now the pirating technique is becoming more sophisticated. That is to say the difference between the first cycle of print&scan image and the second cycle of print&scan image is small. If the above scheme works, the difference between the sequences extracted after the copyrighted image and the forgery must be found. Many repeated experiments (100 times) with the approximately same conditions demonstrate that the mean of the sequence extracted from copyrighted image stabilizes at a certain value M 1 (the variance is between -0.1 and 0.1). Many repeated experiments (100 times) with other conditions different from the copyrighted print and scan show the mean of the sequence extracted from forgery image stabilizes at another certain value M 2 and M 2 is ten times greater than M 1.So M 1 is chosen as the decision threshold. 4 Experimental Results 4.1 Parameter Optimization Channel capacity is a key factor in the watermark insertion and detection. It is well connected with the robustness and the invisibility of the watermark. Robustness need more watermark capacity and invisibility requires capacity should not exceed a certain value. From the point of information theory, MIT lab s Smith and Comiskey [7]

6 Lecture Notes in Computer Science 6 ever made some capacity estimation on the data hiding system. They obtained the conclusion that the channel capacity is proportional to the ratio of signal-noise of the system on the condition that Gaussian noise channel is the basic model of the system and the ratio of signal-noise is low.ramkumar [8] made some improvement on the above model and also made some quantitative analysis. Although this model still have many presumptive conditions, but it offered a useful reflection. In this paper, we used the formula proposed [8] and estimate that we can embed 1000 bits at best robust to first cycle of print&scan in a 256*256 pixel if we just use luminance of the image. For more details [8] can be referred to. The invisibility of a watermark is weighted by the image quality evaluation. PSNR is chosen for simplicity. Generally, the PSNR should be chosen to be 38dB for watermark invisibility and more powerful watermark.the robustness is connected with the following factors:watermark strengthen factor a, watermark sequence repeat times m, watermark sequence length l, etc. PSNR is defined no less than 38dB, the whole length of the adding sequence (8*m*l) is computed to be 1000 at most.the optimized value of a is 0.2 on the condition that watermark sequence is consist of 1, -1, PSNR is 38dB and 8m*l is1000. Of course, the robustness is connected with printing quality and the resolution of the original image. 4.2 Parameter Optimization The most popular attack tool-stirmark3.1 is first selected to test the robustness of the algorithm. The following Table1 is statistical results. The watermark shows good robustness to JPEG compression, scaling, changes in the x-y axis display, removal of the rows and columns symmetrical or not; it shows some robustness on central cropping, rotation with scaling and cropping, x-y direction cropping to some extent; and it is fragile to Linear geometry conversion.the above robustness can satisfy the process of the printing and scanning which includes some rotation (-0.5 degree to 0.5 degree), some cropping (about 1%), scaling, JPEG compression for fast transmission, random error, etc. Test type Test numbers Right Tests numbers Remove the rows and columns symmetrical or not 5 5 Filtering(median Gaussian FMLR sharping) 6 5 JPEG compression Cropping 9 2 Linear geometry conversion 3 0 Change the x-y axis display 8 8 Rotation with cropping,without scaling 16 6 Rotation with cropping and scaling 16 6

7 Lecture Notes in Computer Science 7 Scaling 6 6 x y direction cropping 6 3 Stirmark random bend 1 0 Table 1. Stirmark3.1 test results sum Print&scan Results Figure 4 is a typical result chosen from 100 experiments. It shows bit error rate comparison between the copyrighted and forgery images. As when the bit error rate is lower than 35%, the extracted bit is considered correct. The bit error rate of each bit from the copyrighted image is all below 50%, thus the watermark can be fully extracted. While the bit error rate from the forgery image is above 35%,only about half of the bits can be extracted correctly and now the embedded watemark has become meaningless. So we can make a decision that when the watermark can be 85% or above extracted, the image is considered copyrighted product; otherwise the image will be considered forgery product. Fig. 3. Bit Error Rate Comparison (Copyrighted and Forgery Images) 5 Conclusions The above experiments show that the proposed scheme can satisfy the requirement of forgery preventing for ordinary images. Also it can be used in situations where only the robustness to one cycle of print&scan is needed, such as the ID card, passports, etc. The most excellent point is that the cost of this scheme is largely reduced compared with other forgery techniques and ordinary people can authenticate their products. The combined wavelet and DCT transform is applied to the original image and

8 Lecture Notes in Computer Science 8 the watermark is linearly added to the most energy-concentrated oefficients.the CIE lab color space makes it possible that the watermark technique can be used in forgery prevention field. The repeated experiments for the same watermark and same image under the same parameters are considered on the same environment equipment (including the scanner, printer, etc.). The optimization may vary with different equipment. There is still much work to do from the point of research. If we take the color difference (a* and b*) into account, more watermarks can be added and PSNR will not work. Future work will focus on these. References 1. Joe J. K. Ó Ruanaidh, Thierry Pun, Rotation, scale and translation invariant spread spectrum digital image watermarking, Signal Processing vol. 66(III), pp , May M. Kutter, F. Jordan, F. Bossen, "Digital signature of color images using amplitude modulation", Journal of Electronic Imaging, vol. 7, no. 2, pp , April, C.Y.Lin and S.F.Chang, Distortion Modeling and Invariant Extraction for Digital Image Print-and-Scan Process, ISMIP 99, Taipei, Taiwan, Dec C.Y.Lin, Public Watermarking Surviving General Scaling and Cropping: An Application for Print-and-Scan Process, Multimedia and Security Workshop at ACM Multimedia 99, Orlando, FL, Oct Z.Y.Li, Z.Z.Fu, Hiding information in printing system, CIHW 2000, Beijing, China, Jun I.J. Cox, J. Kilian, T. Leighton and T. Shamoon, Secure Spread Spectrum Watermarking for Images, Audio and Video, ICIP'96, vol. III, pp J. R. Smith and B. O. Comiskey, Modulation and Information Hiding in Images, Workshop on Information Hiding, University of Cambridge, UK, pp , May M. Ramkumar, Data Hiding In Multimedia- Theory And Applications, Ph.D. Dissertation, New Jersey Institute of Technology, Jan. 2000

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