IRJET - A Research on Video Forgery Detection using Machine Learning

The document presents a research on detecting video forgery using machine learning. It proposes a novel approach that uses optical flow and coarse-to-fine detection strategy to detect copy-move image forgery in videos. The approach first divides video frames into overlapping blocks, then extracts GLCM features from blocks. It identifies duplicate blocks using k-means clustering and Euclidean distance calculation. Finally, it detects forged regions in frames by highlighting the duplicate blocks. The approach was implemented and experiments showed it could successfully detect forged regions in videos.