Abstract: Image hashing functions have extensive applications in content authentication, database search and watermarking, etc. A novel perceptual hashing algorithm is developed which is robust to geometric distortions. The algorithm includes three stages: the first stage obtains the image that is invariant to any affine transforms through a normalization procedure; the second stage applies discrete wavelet transform to pseudo-randomly select sub-images to obtain secondary image including main features; the third stage uses singular value decomposing to capture local perceptual features and to get the final hash. The experiments show the method withstands perceptually preserved manipulations including geometric distortions, compression, and common signal processing operations. The content changes are also can be detected accurately. Thus the proposed method achieves perceptual robustness while avoiding misclassification.

Key words: computer application, perceptual Hashing, image normalization, geometric distortions, image authentication