Detection and tracking of moving object using modified background subtraction and Kalman filter

Moving object detection and tracking (MODT) is the major challenging issue in computer vision, which plays a vital role many applications like robotics, surveillance, navigation systems, militaries, environmental monitoring etc. There are several existing techniques, has been used to detect track moving Surveillance system. Therefore it necessary develop new algorithm or modified robust work both day night time. In this paper, BGS technique proposed. The video first converted number of frames, then these frame applied background subtraction with adaptive threshold gives detected object. Kalman filter for experimental results shows proposed method can efficiently correctly objects less processing time compared techniques.