Robust perceptual image hashing via matrix invariants

Robust perceptual image hashing via matrix invariants,10.1109/ICIP.2004.1421855,Suleyman S. Kozat,Ramarathnam Venkatesan,Mehmet Kivanç Mihçak

Robust perceptual image hashing via matrix invariants   (Citations: 47)
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In this paper we suggest viewing images (as well as attacks on them) as a sequence of linear operators and propose novel hashing algorithms employing transforms that are based on matrix invari- ants. To derive this sequence, we simply cover a two dimensional representation of an image by a sequence of (possibly overlapping) rectangles whose sizes and locations are chosen randomly1 from a suitable distribution. The restriction of the image (repre- sentation) to each gives rise to a matrix . The fact that 's will overlap and are random, makes the sequence (respectively) a redundant and non-standard representation of images, but is cru- cial for our purposes. Our algorithms rst construct a secondary image, derived from input image by pseudo-randomly extracting features that approx- imately capture semi-global geometric characteristics. From the secondary image (which does not perceptually resemble the input), we further extract the nal features which can be used as a hash value (and can be further suitably quantized). In this paper, we use spectral matrix invariants as embodied by Singular Value Decom- position. Surprisingly, formation of the secondary image turns out be quite important since it not only introduces further robustness (i.e, resistance against standard signal processing transformations), but also enhances the security properties (i.e. resistance against in- tentional attacks). Indeed, our experiments reveal that our hashing algorithms extract most of the geometric information from the im- ages and hence are robust to severe perturbations (e.g. up to %50 cropping by area with 20 degree rotations) on images while avoid- ing misclassication. Our methods are general enough to yield a watermark embedding scheme, which will be studied in another paper. as the seed of a secure PR number generator in the algorithms) due to the randomness introduced in the signal representation. In this paper, we apply our approach to the problem of image hashing and present several promising results. Moreover, we believe that our approach (or possibly a variant of it) can be extended to ad- dress hashing and mark embedding problems for video and audio as well, with little or no straightforward modications.
Conference: International Conference on Image Processing - ICIP , vol. 5, pp. 3443-3446, 2004
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