Video Forgery Detection Using DWT, Optical Flow and SIFT Methods
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 9
Abstract
Digital video offer many attributes for tamper detection algorithms to take advantage of, specifically the color and brightness of individual pixels as well as the resolution and format. These properties provide scope for the analysis and comparison between the fundamentals of digital forgeries in an effort to develop a better algorithm for detecting tampering in a video. Copy-paste forgery, wherein a region from a video is replaced with another region from the same video (with possible transformations). Because the copied part come from the same video, its important properties, such as noise, color palette and texture, will be compatible with the rest of the video and thus will be more difficult to distinguish and detect these parts. Digital video forensics is a brand new research field which aims at validating the authenticity of videos by recovering information about their history. . Researchers have related the natural issues to the advance in computer graphics, animation, multimedia in the association of high computing machines, algorithms, increases the complexity of the issue. This thesis discusses the copy paste forgery detection in videos using Statistical fingerprints. In this work DWT is used to compress the images and optical flow is used to detect the flow of the moving objects and the forgery object. But the sift technique is used to detect the key features of the original image and the forgery image. The existing algorithm is compared with the new algorithm with precision, recall and total original frame and the detected forgery frame in the input video. In this work 98% accuracy is detected.
Authors and Affiliations
Manpreet Kaur , Er. Mandeep Kaur
Keywords
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