IEEE Int. Conf. on Multimedia & Expo,
July 6-8, 2005, pp. 229-232, Amsterdam, The Netherlands.
Image Authentications Under Geometric Attacks Via Structure Matching
Divyanshu Vats, and
Brian L. Evans
Center for Perceptual Systems,
The University of Texas at Austin,
Austin, TX 78712 USA
Images from Paper -
Presentation Slides -
Image Hashing Research
at UT Austin
Surviving geometric attacks in image authentication is considered
to be of great importance.
This is because of the vulnerability of classical watermarking and
digital signature based schemes to geometric image manipulations,
particularly local geometric attacks.
In this paper, we present a general framework for image content
authentication using salient feature points.
We first develop an iterative feature detector based on an explicit
modeling of the human visual system.
Then, we compare features from two images by developing a generalized
Hausdorff distance measure.
The use of such a distance measure is crucial to the robustness of
the scheme, and accounts for feature detector failure or occlusion,
which previously proposed methods do not address.
The proposed algorithm withstands standard benchmark (e.g. Stirmark)
attacks including compression, common signal processing operations,
global as well as local geometric transformations, and even hard to
model distortions such as print and scan.
Content changing (malicious) manipulations of image data are also
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