A feature-based fingerprinting scheme robust to desynchronization

Gigaud, Guillaume

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https://hdl.handle.net/2142/16905 Copy

Description

Title

A feature-based fingerprinting scheme robust to desynchronization

Author(s)

Gigaud, Guillaume

Issue Date

2010-08-20T18:01:24Z

Director of Research (if dissertation) or Advisor (if thesis)

Moulin, Pierre

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Copyright Protection
• Data Compression
• Digital Fingerprinting
• Feature Extraction
• Image Processing
• Spread Transform Dither Modulation
• SURF Features

Abstract

Traitor-tracing (aka fingerprinting) has received much attention as a possible solution for protecting media copyrights. However, current schemes for image and video fingerprinting lack robustness against geometric attacks. We propose a novel semi-blind fingerprinting scheme that can cope with such attacks. The scheme improves a state-of-the-art high-rate fingerprinting code that can resist tens of colluders and Gaussian noise but has no resistance against geometric attacks. Our scheme uses compressed SURF (Speeded-Up Robust Features) image features as side information in order to estimate and invert any geometric attack in a given class. We consider simple linear attacks (affine transforms), and more complex ones (homography and image warping). Our Estimation-Elimination algorithm estimates the attack parameters by matching image features and eliminating iteratively suspected outliers. We also compare this method to an adapted version of RANSAC (Random Sample Consensus). The fingerprints are embedded securely and invisibly using Spread Transform Dither Modulation (STDM) applied to the intermediate level of a Laplace decomposition of the image. The fingerprints are robust against common attacks such as averaging, interleaving, addition of Gaussian noise, JPEG compression (with quality factor Q=45), cropping (50% of the image area), affine transforms, homography and image warping.

Graduation Semester

2010-08

Permalink

http://hdl.handle.net/2142/16905

Copyright and License Information

Copyright 2010 Guillaume Gigaud

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