SSF fingerprint for image authentication: an incidental distortion resistant scheme

We propose a novel method for image authentication which can distinguish incidental manipulations from malicious ones. The authentication fingerprint is based on the Hotelling's T-square statistic (HTS) via Principal Component Analysis (PCA) of block DCT coefficients. HTS values of all blocks construct an unique and stable "block-edge image", i.e., Structural and Statistical Fingerprint (SSF). The characteristic of the SSF is that it is short, and can tolerate content-preserving modifications while keeping sensitive to content-changing modifications, and can locate tampered blocks easily. Furthermore, we use Fisher criterion to obtain optimal threshold for distinguishing manipulations. The security of the SSF is also achieved by encryption of the DCT coefficients with chaotic sequences. Experiments show that the proposed method is effective for authentication.