Research on Robust Image Perceptual Hashing Technology Based on Discrete Cosine Transform

In this paper, current methods about perceptual hashing were deeply researched and the defects of them were analyzed. Principles and characters of discrete cosine transform, Watson visual model and chaotic model were introduced in details. A new method about perceptual image hashing which combined the characteristics of the three models was designed. This method use discrete cosine transform to feature extraction from image, eigenvector was handled by contrast sensitivity table, Logistic equation was used as chaos sequence generator to encrypt and at last the prediction differential method was used to quantization coding. Experimental results indicated that the method could resist the content-preserving modifications, and possessed strong robustness, safety and retrieval ability, and the collision rate decreases to level 10(-7). Therefore, this technique has the applied value in image authentication, copyright protection, image security and content-based image retrieval and so on.