IMAGE REFINING AND TRACKING

Abstract

Now days in every organization like crime prevention, industrial processes, traffic monitoring, transport safety, control of retail, etc. CCTV cameras are used. In our system we use the videos which are captured by CCTV cameras but to identify the object clearly we divide the videos into the frames. That frames are trying to match with the database images by using face recognition laplacian algorithm. The system is developed in such a way that the customer has to enter image, search, indexing is performed and then start comparing the images one by one. So the set of similar images are displayed. The top rank similar images are then presented to the user. This project is mainly designed considering the scenarios for comparing the images. It is used for image comparison which fulfills exact requirements according to the user Content Based Image Retrieval (CBIR) – the application of computer vision to the image retrieval. CBIR aims at avoiding the use of textual descriptions and instead images based on their visual similarity to a user-supplied query image or userspecified image. CBIR "Content-based" means that the search will analyze the actual contents of the image. The term 'content' in this context refer to colors, shapes, textures as well as the image is sharpen, blurred, edge detect and reset. This report reviewed the main components of a content based image retrieval system, including image feature representation, indexing, query processing, and query-image matching and user's interaction.