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 Laboratory, Center for Perceptual Systems, The University of Texas at Austin, Austin, TX 78712 USA -

Paper - Slides - Software

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 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.

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Last Updated 07/17/06.