Perceptual Multimedia Hashing (Perceptuele multimedia hashing)

Perceptual hashing is a solution for persistent content identification and robust content authentication. The principle of this technique is to extract robust and discriminative features from multimedia data. These features are resistant to incidental distortion, such as compression. They do not vary as long as the content is not significantly changed. They are converted into a compact perceptual hash (PH) value. In this thesis, we provide a comprehensive introduction to perceptual hashing, including the basic definitions, the application scenarios, the security aspects, the design principles, the performance metrics, etc. We clarify different application scenarios and security aspects. We focus on natural scene images and propose several PH algorithms with state-of-the-art performance. We propose three PH algorithms for image content identification. The first one is based on higher-order cumulants. The second one is based on regional features extracted by the angular radial transform. The third one is based on contour features extracted through edge detection. We also derive two video hash algorithms by extending the cumulant-based algorithm. One is suitable for partial video identification. The other is designed for complete video identification. We propose three PH algorithms for image content authentication. The first one is based on the phase of the discrete Fourier transform. The second one is a block-based extension of the first. It facilitates tamper location. The third one is based on the sign bits of a wavelet transform. It is jointly designed with a watermarking algorithm, and can be conveniently embedded in an image. We also propose a PH algorithm for image quality assessment, a framework for security enhancement, and two frameworks for video hash construction.nrpages: 208status: publishe