There is an increase in the requirement of digital image authentication in law, journalism, and medicine, even in the industry. Copy move forgery is the most common method of forgery methods which are applied to digital images. The importance of verifying digital images that are used in important areas with real-time systems is increasing. Taking this need into consideration, in this study, a robust digital image copy move forgery detection method is proposed to realize in real time. The proposed method first extracts the textural form of the input image. The SIFT keypoints and descriptors are obtained from textual images thus more robust keypoints and descriptors will be utilized. Keypoint matching is realized to reveal the image is forged or not and suspicious regions are determined. The localization of forged pixel is realized via Ciratefi based approach. The post-processing step is applied to make the labeling pixels more accurate by utilizing Connected Component Labeling and morphological operation. The GRIP and CMH datasets are used to showing the effectiveness of the state-of-the-art and proposed method. The method is robust to geometric distortion attacks and image degradation attacks. The results indicate that the proposed method has the highest performance especially against geometric distortion attacks suck as rotation and scaling.