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Digital Watermarking With Phase Dispersion Algorithm Team 1 Final Presentation SIMG 786 Advanced Digital Image Processing Mahdi Nezamabadi, Chengmeng Liu,

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Presentation on theme: "Digital Watermarking With Phase Dispersion Algorithm Team 1 Final Presentation SIMG 786 Advanced Digital Image Processing Mahdi Nezamabadi, Chengmeng Liu,"— Presentation transcript:

1 Digital Watermarking With Phase Dispersion Algorithm Team 1 Final Presentation SIMG 786 Advanced Digital Image Processing Mahdi Nezamabadi, Chengmeng Liu, Michael Su

2 Motivating Scenario Alice creates a 3D shape, and publishes it on the web. Bob sells it as his own.Bob sells it as his own. How can Alice prove ownership? (and make Bob pay her a lot of money)How can Alice prove ownership? (and make Bob pay her a lot of money) Alice creates a 3D shape, and publishes it on the web. Bob sells it as his own.Bob sells it as his own. How can Alice prove ownership? (and make Bob pay her a lot of money)How can Alice prove ownership? (and make Bob pay her a lot of money)

3 The solution is… An invisible, robust digital watermark and put it on the image which can be used for proving the ownership. It has been applied in copyright marking business. It can be also applied for digital multimedia

4 Digital Watermarking With Phase Dispersion Algorithm An algorithm for robust, invisible watermarking. Use the spread-spectrum technique which was first in communications for hiding the information. Uses this characteristics to hide and extract information. It can embed both iconic images and binary strings in an image. It can handle various types of attacks.

5 Malicious Attacks Adding noise Adding another watermark Rescale Lossy compression Geometric distortion Cropping Print and scan Adding noise Adding another watermark Rescale Lossy compression Geometric distortion Cropping Print and scan

6 Embedding process illustration

7 Watermark extraction process

8 Indices for image difference MSE (Mean square error) Correlation factor

9 Similarity vs. α Similarity is measured by cross correlation between original and extracted log 64 tiles were used in embedding The α controls the visibility of the watermark logo in the watermarked image The α also depends on the number of tiles

10 Implementation of Binary Message template function 1 embedding binary information consists of representing the one and zero bits by positive delta function and black that are placed in predefined and unique locations within the message image. It consisted of concentric circles with equal increments in radius and random angular displacement. A 64 bits template is shown on left The error rate is 0 for this 64 bits template

11 Implementation of Binary Message template function bits template function is shown on the left 650 bits can embed 32 characters by repeating them 5 times with no compression The error rate is 0.46% for this 650 bits template, that means the probability for get a wrong bit is 9.7e-8

12 Rotation/Scale Detection Thresholding

13 Rotation/Scale Detection Image rotation

14

15 Robustness to lossy compression Original sizeResolutionMSECorrelation Factor 4.1MB2k X 2k pixels Compressed size Compression ratio 555KB KB KB

16 Attacked by low pass filter The watermarked image is blurred The extracted logo is equivalent to original log convolve with a low pass filter

17 Robustness with noise

18 Multiple watermarks With the same keyEmbedded and extracted with different keys

19 Robustness to Cropping

20 Halftoning can destroy the correlation between image and watermark Lena after printed and scanned Extracted watermark

21 Conclusions This algorithm works best under the following circumstances: α = 0.2 gives the best balance between visibility and signal strength. Bigger image size and smaller watermarks ( more tiles). Bigger color depths. The algorithm can resist the following attacks: lowpass filtering, cropping, noise, lossy compression, rotation, rescaling. But it does not handle halftoning. It is sensitive to rotation angles.

22 Future work Deal with printer halftoning attacks Support color images, embed the hiding information in chromatic channels and keep the luminance unchanged. Support Affine transformation to deal with image distortion Make it a stand alone application by integrate the Matlab code with C code

23 Schedule/Timeline Literature search and study -2wks Basic functionality: carrier function, simple iconic image, basic embedding, extraction, invisible wks Embed into multiple-tile images (rotation, scaling resistant) wks Handle cropping wk Binary message and message template function wk Performance evaluation wk Wrap up and Final reports ---1wk Done Done (Partial) Done In progress

24 Thank you Question?


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