Identifying Image Composites by Detecting Discrepancies in Defocus and Motion Blur

Image manipulation has become commonplace in today's social context. One of the most common types of image forgeries is image compositing. In recent years, researchers have proposed various methods for detecting such splicing. Most prior approaches to detecting blur post-processing operation suffer from their inability to identify the spliced region when the background region contained nature blur. In this study, we propose a novel algorithm of detecting splicing in blurred images. We use blur parameters estimation through the cepstrum characteristics of blurred images in order to restore the spliced region and the rest of the image. We also develop a new measure to assist in inconsistent region segmentation in restored images that contain large amounts of ringing effect. Experimental results show efficacy of the proposed method even if the images to be tested have been noised with different levels. Compared with other existing algorithms, the proposed method has better robustness against gaussian noise.