Image authentication using global and local features

Image authentication is the process of proving image integrity and authenticity. Robust hashing method is developed for detecting image forgery which includes removal, insertion of objects, and abnormal color modification. Global, local and shape features are used in forming the hash. Global features are based on Zernike moments which represent luminance and chrominance characteristics of the image. The local features include position and texture information of salient regions in the image. Shape Feature provides an outstanding description of the geometric structure of shapes. Secret keys are introduced in feature extraction and hash construction. The hash value of a test image is compared with that of a reference image. When the hash distance is greater than or less than a threshold, the received image is judged as a forged image. Collision probability is very low.