Geometric distortion-resilient image hashing system and its application scalability

Media hashing is an alternative approach to many applications previously accomplished with watermarking. The major disadvantage of the existing media hashing technologies is their poor resistance to geometric attacks. In this paper, a novel geometric distortion-invariant image hashing scheme, which can be employed to perform copy detection and content authentication of digital images, is proposed. Our major contributions are threefold: (i) mesh-based robust hashing function is proposed; (ii) sophisticated hash database for error-resilient and fast matching is constructed; and (iii) the application scalability of our scheme for content copy tracing and authentication is studied. In addition, we further investigate several media hashing issues, including robustness and discrimination, error analysis, and complexity, for the proposed image hashing system. Exhaustive experimental results obtained from benchmark attacks confirm the excellent performance of the proposed method.

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