Detecting video frame-rate up-conversion based on periodic properties of edge-intensity

Video frame-rate up-conversion (FRUC) is one of the common temporal-domain operations. From the earlier frame repetition and linear interpolation, FRUC has been developed to motion compensated frame interpolation (MCFI), which effectively overcomes the temporal jerkiness and ghosting shadows. In a broad sense, FRUC can be regarded as a video forgery operation. By experiments, it is observed that FRUC still leads to edge dis-continuity or over-smoothing artifacts around object boundaries. In this paper, an edge-intensity based passive forensics approach is proposed to detect the possible FRUC operation in candidate video. After computing the edge intensities of every frame, Kaufman adaptive moving average (KAMA) is exploited to define an adaptive threshold to distinguish the interpolating frames by FRUC from the original frames. Moreover, the original frame-rate of up-converted video can be inferred. Experimental results show that the proposed approach is not only effective for simple frame repetition and linear interpolation, but also valid for advanced FRUC techniques such as MCFI. The detection accuracy is up to 94.5% on average. Its computation is simple as well.