Research On The Technology Of Detecting And Tracking Of Moving Object

Detecting and tracking moving objects is an important part of intelligent monitoring system which inosculates the advanced technologies and research achievements in the domain of computer application such as image processing, pattern recognition, automatic control and so on. It is also an important subject in the area of computer vision and image encoding research, which is popularly used in the area of weapons, shipping navigation, industry monitor and traffic control.In today's world, detecting and tracking moving object in image sequence has become a new hot point. The research object of this paper is image sequence, i.e. video sequence. There is no fixed pattern to detecting and tracking moving objects because of the different environmental conditions and the functions to be implemented, so it is needed to make choice of the already existed algorithm or implement some new algorithm to satisfy the condition to be faced in some situation which is also one of the most popular subjects discussed now.Based on the summary and analysis of the current detecting and tracking moving objects methods, this paper has designed and implemented a system which can detect and track moving object in image sequence after captured. Aiming at the two key parts of object-detecting and object-prediction in video detecting system, a series of algorithms about image segmentation and tracking prediction are adopted, which obtain a better experimental result.When capturing images, this paper adopts the AVICap of multimedia video services in Windows to operate the digital camera to implement the capture of video sequence, which make the system independent of hard device such as video capture card and improve the transportability of the system. When detecting object, image segmentation adopt the improved Otsu algorithm which enhanced the accuracy of system. For image tracking and prediction method, this system adopts an improved algorithm for searching connected area and an algorithm based on Kalman filter which improve both the real-time property and the accuracy of tracking and prediction. In order to detect and track, this paper designs manual and automatic modes which improve the flexibility of the system in some degree. It will display eigenvalue such as the size and the location of the object and show the motion of the camera when the system runs which satisfy the demand of the system.The experimental result shows that the detecting and tracking algorithm used in this system attain the expectable purpose. The algorithm and methods used in this paper will be valued either in the domain of intelligent video control, air surveillance, and industrial detection and so on.