IMPLEMENTATION OF CONTENT BASED VIDEO RETRIEVAL IN MULTIMEDIA APPLICATIONS USING HISTOGRAM DIFFERENCE

The increasing use of multimedia applications nowadays necessitates the development of effective methodologies for manipulating databases storing video, audio information. Moreover, in its beginning stage, content-based access to video scenes requires parsing of each video scenes into its building blocks. The video stream is constitutes number of shots, each shot is a sequence of frames pictured using a single camera. Switching from one camera to another indicates the transition from a shot to the next one. Therefore, the detection of these changes is known as scene transition or shot transition, is the initial step in any video-analysis system. A number of proposed techniques for solving the problem of shot boundary detection exist, 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; thus, its performance has a direct impact on the performance of all other stages. On the other hand, efficiency is also crucial due to the voluminous amounts of information found in video streams. This paper proposes a new robust and efficient paradigm capable of detecting scene changes on compressed .AVI video data. A single core processor takes a lot of time to execute single thread execution of algorithms in a very big video database to overcome this drawback a High performance computing is required (HPC) to make use of GPU for multithreaded execution for video processing algorithms