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

Mar 31, 2015

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Digital Watermarking With Phase Dispersion Algorithm Team 1 Final Presentation SIMG 786 Advanced Digital Image Processing Mahdi Nezamabadi, Chengmeng Liu, Michael Su Slide 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) Slide 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 Slide 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. Slide 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 Slide 6 Embedding process illustration Slide 7 Watermark extraction process Slide 8 Indices for image difference MSE (Mean square error) Correlation factor Slide 9 Similarity vs. Similarity is measured by cross correlation between original and extracted log 64 tiles were used in embedding The controls the visibility of the watermark logo in the watermarked image The also depends on the number of tiles Slide 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 Slide 11 Implementation of Binary Message template function 2 650 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 Slide 12 Rotation/Scale Detection Thresholding Slide 13 Rotation/Scale Detection Image rotation Slide 14 Slide 15 Robustness to lossy compression Original sizeResolutionMSECorrelation Factor 4.1MB2k X 2k pixels0.11940.5130 Compressed size Compression ratio 555KB70.13850.4172 312KB130.15620.3798 199KB200.19010.3251 Slide 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 Slide 17 Robustness with noise Slide 18 Multiple watermarks With the same keyEmbedded and extracted with different keys Slide 19 Robustness to Cropping Slide 20 Halftoning can destroy the correlation between image and watermark Lena after printed and scanned Extracted watermark Slide 21 Conclusions This algorithm works best under the following circumstances: = 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. Slide 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 Slide 23 Schedule/Timeline Literature search and study -2wks Basic functionality: carrier function, simple iconic image, basic embedding, extraction, invisible ----------- 2wks Embed into multiple-tile images (rotation, scaling resistant) ---------------2wks Handle cropping ----------------1wk Binary message and message template function----------------------------1wk Performance evaluation ------1wk Wrap up and Final reports ---1wk Done Done (Partial) Done In progress Slide 24 Thank you Question?