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Secure Spread Spectrum Watermarking for Multimedia

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Secure Spread Spectrum Watermarking for Multimedia Powered By Docstoc
					                   Secure
          Spread Spectrum
Watermarking for Multimedia

               Ishani Vyas
         CS590 Winter 2008
Agenda
   To explain about watermarking
    characteristics
   How to insert watermark in spread spectrum
   Structure of the Watermark
   Experimental Result
Characteristics of Watermarking
  Unobtrusive
  Perceptually invisible or presence should not interfere with work being
   protected
 Robust
  Difficult to remove. May be removed sufficient knowledge of the process of
   insertion. Available of Partial Knowledge-Result in degradation in data
   fidelity.
 Watermark should be robust to
     Common Signal Processing-should be retrievable even if its operations
   are applied to the data. For example D/A&A/D conversion,resampling
   ,requantization.
  Common geometric distortions (image and video data)- Watermarks in
   image and video data should be immune from geometric image operations
   such as rotation, translation, cropping and scaling
 Collusion and Forgery- Watermark should be robust to collusion by multiple
   individuals who each posses a watermarked copy of data.
Cont
Watermark should be robust to combining copies of
  same data set to destroy the watermarks
 Universal – apply same digital watermark algorithm to all
  three media under consideration.
 Unambiguous- Retrieval of the watermark should
  unambiguously identify the owner.
Why need of Spread Spectrum
watermarking
   The previous methods have not explicitly identified the perceptually
    most significant components of a signal as the destination for the
    watermark.
   Key insight of this paper is that the watermark must be placed in
    perceptually significant regions of the data despite the risk of
    potential fidelity distortions.
   Apply watermarking in significant spectral components of a signal.
   How common signal transformations, (i.e compression, quantization
    and manipulation) affects the frequency spectrum of a signal.
   Watermark should be embedded in the data`s perceptually
    significant frequency components.
   But how to insert watermark into significant components of
    frequency spectrum without any distortions.
Watermarking in frequency
domain
   Lossy compression is an operation that usually eliminates
    perceptually non-salient components of an image or sound.
   To preserve watermark in the face of such an operation, watermark
    must be placed in the perceptually significant regions of the
    data.Data loss usually occurs among the high frequency
    components .
   Geometrics distortions specific to image and video.(Rotation,scaling
    ,translation,cropping)- minimum 4-9 points between the original and
    the distorted watermark image..Again loss of data at high frequency
    spectral regions of the image.
   Common signal distortion(D/A&A/D, resampling ,requantization,
    including dithering and recompression and common signal
    enhancements to image contrast/or color)
Spread Spectrum coding of
watermark
   How to insert the watermark into most significant region
    of an spectrum without such alteration become noticable.
Structure of Watermark
Experimental Result
Watermarked image
Experiment 1:Uniqueness of
Watermark
Experiment 2:Image Scaling
Experiment3: JPEG coding
distortion
Experiment 4:Dithering
Distortion
Experiment 5:Clipping
Experiment 6:Print ,Xerox or
scan
Experiment 7:Attack by
watermarking watermarked image
Experiment 8:Attack by
collusion

				
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