Abstract
In this paper, a multi-resolution Weber law descriptors (WLD) based image forgery detection method is introduced. Due to the maturing of digital image processing techniques, there are many tools, which can edit an image easily without leaving obvious traces to the human eyes. So the authentication of digital images is an important issue in our life. The proposed multi-resolution WLD extracts the features from chrominance components, which can give more information that the human eyes cannot notice. A support vector machine is used for classification purpose. The experiments are conducted on a large image database designed for forgery detection. The experimental results show that the accuracy rate of the proposed method can reach up to 93.33 % with multi-resolution WLD descriptor on the chrominance space of the images.