Statical analys to supply chain management

Key Words: Video indexing, Video segmentation, Rapid access to video databases, Semantic retrieval of video Today, the use of digital videos instead of analog videos has become most popular in terms of easily recordable and low-cost storage. Therefore, huge amount of digital video archives have been came out dramatically. In order to access this video database very fast, the semantic search in a video has been an important demand. While the standard picture and text searching methods cannot be used in a digital video, the video indexing has become a popular interest, and lots of research have been came out. Digital video indexing methods are implemented by segmenting the videos into sub-scenes and extracting the main data related to these sub-scenes. In this sense, correct video segmenting has been most important part of the video indexing. In this study, video segmenting algorithms about uncompressed videos have been investigated and compared with their performance analysis. An interface software has been designed for making the practical applications of these segmenting algorithms possible. Also different interface software has been designed for comparing the performance analysis of the segmenting algorithms automatically and giving the results to the user in graphically and numerically. Added to these, an algorithm called Filtered Video Histogram Comparison has been implemented which has more successful segmenting results than existing video segmenting algorithms.