The existing digital image editing tools have made the authentication of  digital

images an important issue.  The objective of this paper is to propose an image

authentication scheme, which is able to detect malicious tampering while tolerating some

incidental distortions.  By modeling the magnitude changes caused by incidental distortion

and malicious tampering as Gaussian distributions with small and large variances,

respectively, we propose to embed a watermark by using a mean quantization technique

in the wavelet domain. The proposed scheme is superior to the conventional quantization-

based approaches in terms of the credibility of authentication. Statistical analysis is conducted

to show that the probabilities of watermark errors caused by malicious tampering and

incidental distortion will be, respectively, maximized and minimized when our new scheme

is applied. Experimental results demonstrate that the credibility of our method is superior to

that of the conventional quantization-based methods under malicious attack followed by an

incidental modification, such as JPEG compression, sharpening or blurring.

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