This paper proposes an image authentication method that detects tamper and localizes tampered areas efficiently. The efficiency of the proposed method is summarized as the following three points. 1) This method offers coarse-to-fine tamper localization by hierarchical data hiding so that further tamper detection is suppressed for blocks labeled as genuine in the uppper layer. 2) Since the image feature description in the top layer is hidden over an image, the proposed method enciphers the data in the top layer rather than enciphers all data in all layers. 3) The proposed method is based on the reversible data hiding scheme that does not use highly-costed compression technique. These three points makes the proposed method superior to the conventional methods using compression techniques and methods using multi-tiered data hiding that requires integrity verification in many blocks even the image is genuine. Simulation results show the effectiveness of the proposed method.

This paper proposes a novel reversible image authentication method that does not memorize the parameters for extracting embedded authentication data from an image. The proposed method once distorts an image to hide data for authentication into the image, it recovers the original image from the distorted image unless tamper is applied to the image, i.e., reversible. By comparing extracted data and data generated from the restored image, this method detects image tampering and further localizes tampered regions by the unit of block. The proposed method extracts hidden data without memorization of parameters used in its algorithm. This feature makes the proposed method practical. Whereas any method memorizing parameters faces severe problems with storage and management of parameters, according to the increase in the number of memorized parameters that is caused by serving accurate tamper localization and/or by applying itself to a huge number of image collection, e.g., video sequences. Simulation results show the effectiveness of the proposed method.