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Review of : Spread Spectrum Image Watermarking

Review of : Spread Spectrum Image Watermarking. Presenting: Rani Hoitash. Presentation Outline . The growing need for watermarking Basic encryption techniques and limitations Important factors for watermark Overview of visual models Watermarking techniques Spread Spectrum watermarking

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Review of : Spread Spectrum Image Watermarking

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  1. Review of : Spread Spectrum Image Watermarking Presenting: Rani Hoitash

  2. Presentation Outline • The growing need for watermarking • Basic encryption techniques and limitations • Important factors for watermark • Overview of visual models • Watermarking techniques • Spread Spectrum watermarking • Watermarking and the Internet • Current applications • Conclusion

  3. Motivation • Digital data can be copied without compromising the quality of the copied object. • Digital objects can be copied and distributed anonymously with no way to identify the criminals. • Copyright protection of multimedia data is essential for network data delivery. • Number of watermarking publication grew from 2 in 1992 and 1993 to 64 in 1997[1].

  4. Encryption Techniques • Public key cryptography involves two keys a private and a public key that are mathematically related so that a message encrypted with one can be decrypted with the other. • Private key or symmetric key cryptography:every user possess only one type of key, which is being used for the encryption, and decryption of messages.

  5. Certificate Authority (CA) Services • security of data, privacy of data, business policies, and transaction processing integrity • they provide a public key certificate, which is a digital document that irrevocably binds a person’s identity to a public key • Time stamping services • well established CA’s are BBB online, Truste, Veri-Sign, ICSA, and Web-Trust[16].

  6. Limitations of Encryption Techniques • Although encryption protects content through the delivery process, once the content is decrypted the data is no longer protected and therefore can be copied and distributed without compromising the identity of the participants. • Watermarking and encryption should be used as two complimentary techniques

  7. Definition of Digital Watermark • A digital watermark is a visible or perfectly invisible, identification code that is permanently embedded in the data and remains present within the data after any decryption process[4]. • makes possible to identify the source, author creator owner, distributor, and authorizes consumer of digitized images [4] .

  8. Important Factors for Watermarking • Difficult to notice (transparency). • to place it in the most insignificant parts of the image • contradicts the requirements for robustness • The limitation of compression algorithms[6]

  9. Important Factors for Watermarking • Robustness • robust to transformations that include common signal distortions as well as digital to analog and analog to digital conversion, and geometric distortions. • The watermark should be present in the data after distortion • The watermark detector should be able to detect the watermark.

  10. Important Factors for Watermarking • Tamper Resistance • The same image might be distributed with different watermarks for the purpose of buyer identification. • Threat: Buyers may collude in an attempt to tamper the watermark. • The watermark should be tamper resistance.

  11. Important Factors for Watermarking • Capacity • Multiple identifiable watermarks • Universal • The same digital watermark should apply for all three multimedia objects. • Scalability • the cost of decoding is very important • should support real time decoding

  12. Visual Models • By incorporating perceptual knowledge into the watermark scheme it is possible to insert the watermark into most significant part of the image • Use of the visual models provide thresholds for how much a given transform coefficient can change before such changes are noticeable

  13. Frequency sensitivity • sensitivity mainly uses Modulation Transfer Function (MTF). This function describes the human eye's sensitivity to sine wave at various frequencies. • Given that the minimum viewing distance is fixed it is possible to determine a static just noticeable difference (JND) threshold for each frequency band. • This frequency sensitivity technique provides a basic visual model that depends only on the viewing conditions and is independent of image content.

  14. Visual Models (Cont..) • Luminance Sensitivity: a way to measure the effect of the detectability threshold of noise on a constant background. • Contras Masking: Contrast masking refers to the detectability of one signal in the presence of another signal.

  15. Discrete Cosine Transformation (DCT) • . The DCT has become the standard method for image compression • typically the image is divided into 8x8 pixel blocks, where each block is transformed into 64 transform coefficients

  16. Spatial watermarks • Spatial watermarks provide simple and effective schemes for embedding an invisible watermark into the original image • they are not robust to common image alteration. • resulting image of high quality but not robust to attacks. Spatial watermarking techniques include the checksum technique, and the basic spread spectrum approach.

  17. Spatial watermarks(cont.) • Checksum Technique • formed of the values of the seven most significant bits of all pixels in the image.

  18. Spread Spectrum Communication. • Spread spectrum system is one in which the transmitted signal is spread over a wide frequency band. • The codes used for spreading have low cross correlation values and are unique to every user.

  19. Advantages of Spread Spectrum Communication • Resist intentional and unintentional interference. • Can share the same frequency band with other users (multiple watermark). • Protect the privacy, due to the pseudo random code sequence.

  20. Secure Spread Spectrum Watermarks for Multimedia • spread spectrum watermark based on DCT [4] . • Cox et al asserted that in order for a watermark to be robust, it need to be placed in the most significant part of the image. • the watermark will be composed of random numbers drawn from a Gaussian N(0,1) distribution

  21. Secure Spread Spectrum Watermarks for Multimedia General procedure: • Applying frequency transformation to the data. • Computing perceptual mask to highlight the most significant regions in the spectrum that can support the watermark without affecting the image fidelity (V).

  22. Secure Spread Spectrum Watermarks for Multimedia • Inserting the watermark to the image. • Inverse DCT

  23. Secure Spread Spectrum Watermarks for Multimedia Watermark Structure A watermark consists of a sequence of real numbers X=x1……Xn where each value xi is chosen independently according to N(0,1).

  24. Secure Spread Spectrum Watermarks for Multimedia • A sequence of values V=v1....vn is extracted from each document D. The watermark xi is then inserted into the value vi and results in V’=v’ 1...v’ n . • . V’ is inserted to the image instead of V and the result is document D’ • An attacker might alter document D’ into D*. Given D and D* watermark X* is extracted and is compared to X for statistical significance

  25. Secure Spread Spectrum Watermarks for Multimedia Insertion of the watermark • v’i=vi (1+aixi) where a is a parameter which determines the extent to which X alters V. • The author does not provide a solution for how to compute a in order to maximize the robustness of the watermark.

  26. Secure Spread Spectrum Watermarks for Multimedia Evaluating the similarity of the watermark • The extracted watermark might differ from the original watermark. • sim(X,X*)= X*·X/SQRT(X*·X*) • one should decide on a threshold T, and compare sim(X,X*)>T • Set T to minimize the false positives and false negatives. • This requires the independence of X*,X

  27. Image and Watermarked Image

  28. Uniqueness of the Watermark

  29. Image Scaling The watermark is still noticeable on the small image.

  30. Experiment (Cont.) • JPEG distortions • Dithering distortions • Cropping • Xerox and Scan • Adding multiple watermarks

  31. Disadvantages • The need to have the original image to be able to detect the watermark. • Since the DCT transform is based on the whole image , the transform does not allow for any local spatial control of the watermark. • Does not provide a maximum use of the human visual system

  32. Image Adaptive Watermarking • Wolfgang et al [1]developed this model based on [4]. • The image adaptive DCT algorithm is based on 8x8 DCT framework which allows to incorporate visual masking effects. • All local information is extracted from the visual models stored in a Just Noticeable Difference (JND) Matrix.

  33. Image Adaptive Watermarking • The JND is derived from image independent frequency sensitivity and image dependent luminance sensitivity and contrast masking. • This assists in determining the maximum amount of watermark signal the can be tolerated.

  34. Image Adaptive Watermarking X u,v,b + J u,v,b W u,v,b X u,v,b >J u,v,b X*u,v,b = X u,v,b, otherwise • where X u,v,b refers to the coefficient in position (u,v) of block b, X* u,v,b is the watermarked DCT coefficients, W u,v,b is the sequence of watermark values and Ju,v,b is the computed Just Noticeable Difference.

  35. Image Adaptive Watermarking • The watermark insertion is not limited only to the most significant part of the image , the goal is to place the maximum strength watermark sequence.

  36. Detection • W*s,u,v,b= Xu,v,b- X*u,v,b • W*u,v,b = W*u,v,b,s/Ju,v,b • Pww*= (w*w)/(w*w*) • The probability Pww which is a normalized correlation coefficient between the two signals w and w* is used to check the threshold for the watermark detection. • Again P is examined against a threshold which is designed to balance false positives and false negatives.

  37. Experiment • In the first image the figures are fairly uniform, therefore we cannot take full advantage of the image adaptive watermark. • In the second image the content is non uniform a fact that allows us to take full advantage of the image adaptive watermark.

  38. JPEG Compression

  39. Rescaling

  40. WWW Applications • trusted third parties • A valid public key with registered identity. • Transfer the image to the third party (watermarking server). • The server verify that there are no previous watermarks and timestemps. • The server embed the watermark and a timestamp into the image and save it . • The server encrypts the watermarked image and the unique id with the customer’s public key, and sends it to the customer.

  41. WWW Applications (Cont.) • The watermark is searching the internet on a continuos basis and look for watermarked images. • The watermark server issues a report to the image owner regarding the location of all the copies of the image. • It is crucial to have a standard watermarking technique, so that watermarked can be identified by multiple certificate authorities.

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