Scene change detection by feature extraction from strong edge blocks

Abstract

An algorithm is proposed for the detection of scene changes in video sequences. The algorithm is based on the comparison of several features which represents the characteristics of frames. More specifically, the feature extraction is confined to several blocks that contains strong edges instead of the overall image as in the conventional algorithms, in order to concentrate more on the important colors and objects than the backgrounds. Several non-overlapping blocks of predefined size are first found, which contain strong edges in the frame. Then, three different kinds of features are extracted by using the pixels in the blocks. One is the color histogram of pixels in the blocks, the second one is the sum of absolute difference (SAD) between the blocks of current and previous frame as in video coding, and the third is the number of active blocks, which have the edge strength larger than a given threshold. The dissolve and wipe are detected by comparing the histogram of the blocks, the cut is detected by the SAD, and fade-in/outs are detected by the number of active blocks. The comparison of several test sequences shows that the color histogram from the strong edge blocks is a promising feature for detecting wipes and dissolves. Also, cut detection performance by the SAD of strong edge blocks is shown to be comparable to the conventional feature based algorithm. The fade-in/outs are also easily detected with high precision, by counting the number of active blocks.