Proc. IEEE Int. Conf. on Image Processing,
Oct. 24-27, 2004, vol. 3, pp. 677-680, Singapore.
Robust Perceptual Image Hashing Using Feature Points
Vishal Monga and
Brian L. Evans
Embedded Signal Processing
Center for Perceptual Systems,
The University of Texas at Austin,
Austin, TX 78712 USA
Image Hashing Research
at UT Austin
Perceptual image hashing maps an image to a fixed length binary string
based on the image's appearance to the human eye, and has applications
in image indexing, authentication, and watermarking.
In this paper, we present a general framework for perceptual image hashing
using feature points.
The feature points should be largely invariant under perceptually
To satisfy this, we propose an iterative feature detector to extract
significant geometry preserving feature points.
We apply probabilistic quantization on the derived
features to further enhance perceptual robustness.
The proposed hash algorithm withstands standard benchmark (e.g.
including compression, geometric distortions of scaling and small
angle rotation, and common signal processing operations.
Content changing (malicious) manipulations of image data are also
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