Comparative Study of Block Matching Algorithm and Dual Tree Complex Wavelet Transform for Shot Detection in Videos

Various methods of automatic shot boundary detection have been proposed and claimed to perform reliably. Although the detection of edits is fundamental to any kind of video analysis since it segments a video into its basic components, the shots, only few comparative investigations on early shot boundary detection algorithms have been published. A vast number of proposed techniques exist for shot boundary detection but the major criticisms to them are their inefficiency and lack of reliability. The reliability of the scene change detection stage is a very significant requirement because it is the first stage in any video retrieval system. This paper gives a comparative study of Block Matching Algorithm (BMA) and Complex Wavelet Transform (CWT) algorithm. BMA uses motion vectors to detect shot transition in videos and CWT uses edges of the objects, are invariant to illumination changes. The algorithm performance is measured in terms of hit rate, number of false hits, and miss rate for hard cuts, fades, and dissolves over a large and diverse set of video sequences.