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Robust perceptual image hashing using feature points

12 years 3 months ago
Robust perceptual image hashing using feature points
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 insignificant distortions. 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. Stirmark) attacks including compression, geometric distortions of scaling and small angle rotation, and common signal processing operations. Content changing (malicious) manipulations of image data are also accurately detected.
Vishal Monga, Brian L. Evans
Added 24 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2004
Where ICIP
Authors Vishal Monga, Brian L. Evans
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