Enhance Detection Method for Identifying Orthogonally Rotated or Flipped Pasted Region in an Image

With the widespread availability of image manipulating software and with ease of use, anyone with basic knowledge can modify the image without leaving any traces in the image. People believe in whatever they see in an image, but it is not necessary that the content has to be real. With the wide use of social media people with malicious intent share images that are modified and make you believe that they are real and by doing so they can influence people's opinion which is a grave danger for society. In copy paste attack a part of the image is copied and pasted on to a different region of the same image, this pasted region can be detected by using the block-based method, but when the copied region is rotated orthogonally or if it is flipped before pasting on to the destination, such pasted regions are impossible to detect with the block-based approach. In this paper we are proposing a new technique to detect rotated or flipped pasted regions in an image and the performance of this new technique is compared with the SVD (Singular Value Decomposition) method used for the same purpose. The proposed new technique overcomes the rounding off errors in singular values of SVD method and computationally efficient than SVD and also computes the angle of rotation