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Image perceptual hashing finds applications in content indexing, large-scaleimage database management, certification and authentication and digitalwatermarking. We propose a Block-DCT and PCA based image perceptual hash inthis article and explore the algorithm in the application of tamper detection.The main idea of the algorithm is to integrate color histogram and DCTcoefficients of image blocks as perceptual feature, then to compress perceptualfeatures as inter-feature with PCA, and to threshold to create a robust hash.The robustness and discrimination properties of the proposed algorithm areevaluated in detail. Our algorithms first construct a secondary image, derivedfrom input image by pseudo-randomly extracting features that approximatelycapture semi-global geometric characteristics. From the secondary image (whichdoes not perceptually resemble the input), we further extract the finalfeatures which can be used as a hash value (and can be further suitablyquantized). In this paper, we use spectral matrix invariants as embodied bySingular Value Decomposition. Surprisingly, formation of the secondary imageturns out be quite important since it not only introduces further robustness,but also enhances the security properties. Indeed, our experiments reveal thatour hashing algorithms extract most of the geometric information from theimages and hence are robust to severe perturbations (e.g. up to %50 cropping byarea with 20 degree rotations) on images while avoiding misclassification.Experimental results show that the proposed image perceptual hash algorithm caneffectively address the tamper detection problem with advantageous robustnessand discrimination.

A Novel Block-DCT and PCA Based Image Perceptual Hashing Algorithm