Video Shot Boundary Detection using Graph Theory

Abstract

Video-Shot boundary detection has attracted much more research interesting in recent years. Shot change detection is the procedure for identifying changes in the scene content of a video sequence so that alternate representation may be derived for the purposes of browsing and retrieval. e.g. key frames may be extracted from a distinct shot to represent it. A video is defined as a continuously imaged temporal segment of a video. It is themost effective media for capturing the world around us. The recent explosive growth of digital video application entails the generation of vast amount of video data. Shot is defined as a part of the video that result from one continue recording by single camera. Shot boundary detection is the procedure for identifying changes in the scan content of a video sequence so that attenuate representation may be derived for the purpose of browsing and retrieval. Many algorithms have been proposed for detecting video shot boundaries and classifying shot and shot transmission types. Detection of gradual transition and elimination of disturbance caused by illumination change, fast object and camera motion are the major challenges of shot boundary detection. This paper presents a novel approach to address this challenge. In this, a video shot boundarydetection using graph theory approach is use. First, the video is converted into its frames and then feature of colors is extracted from each frame to compute dissimilarity between frames. Lastly, video frames are divided into several different groups through graph theory algorithm. According to cut and gradual changes, they have different characters in the two successive frames belonging to different groups; it detects cut and gradual shot.