An improved algorithm for shot cut detection

The increasing availability and use of online video has led to a high demand for very accurate and efficient automated video analysis techniques. Previous research has concentrated on segmenting videos by detecting the boundaries between camera shots. Shot cut detection is the first step in every video indexing and retrieval algorithm. A number of automated shot-change detection methods for indexing a video sequence to facilitate browsing and retrieval have been proposed in recent years. However, there is no dataset that is internationally agreed upon to be used as a benchmark for evaluating the emerging techniques. In this paper, a new algorithm is proposed for the shot cut detection. The detection algorithm consists of three major stages. The morphological Hit-Miss transform is applied in the first stage. The watershed transform is applied next and finally feature extraction is carried out. To enable comparison with previous work, the dataset used in this new algorithm is applied to the technique introduced by T. Y. Liu et al.,2004. Our algorithm shows a remarkable difference and it provides a better recall and precision rates.