Tamper Detection using Watermarking Scheme and K-Mean Clustering for Bio Medical Images

In this paper, we focus image authentication and tamper detection using K-mean clustering based on fragile watermarking scheme. The two important aspects of the authentication watermarking scheme are Tamper detection and localization accuracy. In our scheme, clustering values of the watermarked image used as secret key. It can be detect any amendment is made to image and also point out the exact location that have been modified. Significant features of the schemes are reducing the time complexity and improving the PSNR value , with stand attacks. Original image is not required for verification