Mean quantization blind watermarking for image authentication

The objective of this paper is to propose an image authentication scheme, which is able to detect malicious tampering of images even they have also been incidentally distorted. By modeling incidental and malicious distortions as Gaussian distributions with small and large variances, respectively, we propose to embed a watermark in the wavelet domain by a mean quantization technique. Due to the various probabilities of tamper response at each scale, these responses are integrated to make a decision on the tampered areas. Statistical analysis is conducted and experimental results are given to demonstrate that our watermarking scheme is able to detect malicious attacks while tolerating incidental distortions.