Copy-move forgery detection using zernike and pseudo zernike moments

Despite the fact that images are a primary source of information, the rapid growing of tools that used to amendment images makes the reliability of the digital images in risk. Copy-Move forgery is one important method to forge an image; where part of the image is copied and pasted in another part of the same image. Regarding the related literature in this topic, many methods were developed to detect Copy-Move forgery; each method has its own strengths and weaknesses. In this paper, the capability and the efficiency of using Pseudo-Zernike Moment (PZM) and Zernike Moments (ZM) in detecting this type of forgery are tested. For evaluating the performance of these methods, comprehensive and authentic dataset is used for testing purposes. The results showed that both methods (PZM-based and ZM-based) are robust against blurring, noise adding, color reduction, brightness change, and contrast adjustments that may affect the image with an acceptable false match. However, rotated and scaled copied region still give weak results. Moreover, the PZM-based method is slightly faster and more accurate than ZM-based method.