An approach for object detection and object tracking using background subtraction

Abstract

The video established object tracking and detection contracts by non-stationary image stream that shift over time. Strong and real-time moving objects detection are difficult problem in computer vision research area. Identifying moving objects from a video sequence is a critical task in computer vision application. In the existing system researchers have designed a modified PN learning algorithm for enhancing the performance of system. Modified PN learning algorithm achieves performance to increase frame processing by adding background subtraction technique for any real-time object detection to track single object in video stream. Existing system works poor for multiple moving object detection. The proposed system is too designed for multiple moving objects tracking in real-time. In proposed system we use background image update, color segmentation and edge detection technique. There are problem in tracking real-time multiple object through a sequence of video. Thus, we solve this problem by different technique that has been proven to be a strong algorithm to any real-time moving object.