Robust image hashing with tampering recovery capability via low-rank and sparse representation

Multimedia hash is an effective solution to image authentication and tampering identification. We propose an image hashing scheme based on Low-Rank and Sparse Representation. Low-Rank Representation is applied to the attacked image to obtain image feature matrix and error matrix. Then the properties of dimension reduction and tampering recovery inherent in Low-Rank Representation and Compressive Sensing are exploited for hash design. We use Compressive Sensing to recover the primary feature of image. Furthermore we use Low-Rank Representation to recover the image from tampering. Thanks to the error correction and structure recover capabilities of Low-Rank Representation, experiments reveal that our proposed hashing scheme is robust to content preserving modifications and has better image recovery performance compared with existing hashing schemes.

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