A Fast Detection Method for Frame Duplication Forgery based on Correlation

In recent years, fast development of video editing software has made video forgery applicable. One of the most frequently encountered forgery types in video forensics is the frame duplication forgery. Researches have proposed methods to deal with this type of forgery. The two main drawbacks of this methods reported in the literature are execution time and low detection accuracy. In this work a new frame duplication forgery detection method that uses correlation between neighboring frames to extract features from video is proposed. Experimental results show that the proposed method has lower execution time with better detection accuracy compared to similar works reported in the literature.