Shot Boundary Detection Using HSV Colormap for Content Based Video Retrieval

Abstract

I.INTRODUCTION Rapid developments of digital video capturing and editing devices and technology have been producing an ample of digital video data every day. As a consequence, digital video data information keep on increasing everyday and so need of an efficient application arrives; such as video-on-demand or content based video retrieval. This technology of how to catalogue and retrieve videos on demand for future re-use becomes a need of society. In automatic management of video database, it is practically inappropriate to use keywords to describe each video sequence because this annotation process asks for enormous human power; in addition keywords used cannot describe the subject properly. Hence, to fulfil this demand of retrieving similar videos from the database, we need a system Content based video retrieval which retrieves the same videos based on video content analysis. Primary tasks of CBVR system are shot boundary detection, key-frame extraction. Shot boundary detection becomes the groundwork for video retrieval and management. Shot boundary detection is allowing the computer to discover the editing positions and produce the original shot sequences. The detected shots will become the basic query units in video retrieval systems. Video is a space and time varying structure captured by either single camera or multiple cameras. Video structure can be divided as video scenes, video shots, video frames and video key frames. All play a major role for video indexing and video retrieval applications. A video shot is a succession of frames captured by a single camera in a continuous run. Video shot is a group of sequence of similar action frames which carries almost same information and visual features such as colors, motions and textures. The visual information of each shot of the video can be described by one or multiple frames, called key-frames. The number of keyframes cannot be predetermined because of content variation. In case of a static shot there is little content variation, so a single keyframe can describe the whole shot effectively, whereas in case of a high camera editing and object motion shot, we may need more key-frames for a better representation of a video content (Vasileios T. Chasanis Jan. 20093). Video shot boundary detection is a primary step in video indexing and retrieval, and in general video database management. Shot boundary detection is used to segment a given video into its continuous shots in a way it was produced, and to classify and detect the different shot transitions (Don Adjeroh May. 20094). Different algorithms have been proposed, based on color histograms (Ballard 1991, Tanaka 19925), pixel color differences (H. Zhang 1993), color ratio histograms (Lee 1997), edges (R. Zabih 1999), and motion. In this proposed work, we studied the problem of video shot classification and separation using statistical features of HSV color map without calculating statistical threshold. Manual change of threshold is not a practical solution for shot boundary detection. Proposed approach does...