Research On Image Hashing Technology For Authentication Based On Finite Ridgelet Transform

Image hash has been paid much attention in recent years for its extensive applications in content authentication, database search and watermarking. During the manipulations of content-preserving, such as compression, filtering, geometric distortion and so on, traditional cryptographic hashes are sensitive to any change of bit and not applicable to images. So it is necessary to research on the image hash to make it robust to content-preserving manipulations and able to detect the malicious attacks.Currently, image hashing algorithms are mainly implemented in transform domains. Wavelet is mostly used as one of them. However, wavelet is usually suitable for zero degree(point) singularities and the ID singularities existed in images affect the efficiency of feature extraction in the wavelet domain making it difficult to generate an ideal image hash.Finite ridgelet transform, which is 1D wavelet transform along each direction in the finite radon transform domain, has shown its advantage in linear detection and image reconstruction. However, papers in demonstrating applying finite ridgelet transform to image hashing algorithm are few. In this dissertation, the author has made some research and attempt to do so. The main innovations are as follows:(1)An image hashing based on finite ridgelet transform and fourier transform is proposed. At first, it preprocessed the original image and partitioned the image into blocks. Second, it made ridgelet transform for each image block and then made 1D FFT transform along each direction in the ridgelet transform domain. Finally, it extracted the maximum value of ridgelet coefficients and the sum of FFT amplitudes to generate the hash value. Compared with some other hashing methods, the ridgelet-based hash has better robustness against JPEG compression, salt & pepper noise, gaussian lowpass filtering, rotation, scale and so on. Since a key is used in the algorithm, the hash is harder to be forged.(2)To obtain more robust and secure image hash value, a novel image hashing scheme based on human visual system is proposed. It first preprocessed the original image, then extracted ridgelet coefficients based on frequency sensitivity in the human visual system to generate the hash value. The experimental results demonstrate that the scheme has a good performance against JPEG compression, filtering, adding noise, shearing, rotation and scale. The hash has good robustness, sensitivity and security.