Robust perceptual image hashing via matrix invariants

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 invariants. 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 (representation) 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 crucial for our purposes. Our algorithms first construct a secondary image, derived from input image by pseudo-randomly extracting features that approximately capture semi-global geometric characteristics. From the secondary image (which does not perceptually resemble the input), we further extract the final features which can be used as a has...

• Type: Conference
• Year: 2004
• Where: ICIP
• Authors: Mehmet Kivanç Mihçak, Ramarathnam Venkatesan, Suleyman Serdar Kozat
• Keywords: ICIP 2004, Image Processing, Pseudo-randomly Extracting Features, Secondary Image, Singular Value Decomposition, Spectral Matrix Invariants, Watermark Embedding Scheme