A Method of Video Shot-Boundary Detection based on Grey Modeling for Histogram Sequence

Video Shot-Boundary Detection is important for video analysis, segmentation and retrieval. The detection results of Shot-Boundary are not only relation with two nearest frames of shot cuts, but also their several neighboring frames. Video stream is multistream time sequence. Grey model based on set sequence (SGM) is proposed to analyze and process multi-stream time sequences constructed with sampled histograms in this paper. Consequently, a novel Shot-Boundary Detection method is put forward based on SGM and color histogram, which includes the following steps: (1) When a new video frame coming into the detection system, the image is transformed into intensity image under HSI color model; (2) Histogram of the video frame can be obtained. Then, taking samples for the histogram and constructing set sequence with proximate sampled histograms is implemented; (3) SGM is introduced to simulate the sampled histogram sequence in this detection method. Moreover, absolute mean error (AME) and regulative AME (RAME) with thresholds are applied to make a detection judgment. Finally, the experiments illuminate that the proposed method is an effective Shot-Boundary Detection method, and it is superior to method of Histogram disparity significantly, especially when it is used to detect cuts with some complex video scenes.