The theses propose some approaches for real-time tracking of the moving object, including the image extraction and object tracking. The methods of image extraction locate the center of the object by using average and variance brightness of the block pixel. Also, we combine the scheme of object-center-location and block-full-search to focus the central position of the object. Additionally, the control methods of object Tracking make use of P (Position) type, PV (Position -Velocity) type, PVA (Position-Velocity-Acceleration) type, and improved PVA-type controllers to achieve the goal. However, The methods of average and variance brightness of block pixel not only can reduce the sampling error of the camera but also fit the higher contrast environment. The thesis also brings up vertical relationship method to get more correct extract information of the moving object. The four kinds of tracking controllers use different algorithms to estimate the next position of the object based on the error value and the change of error value. Finally, we analyze and compare the performance of all the proposed methods as indicated in simulation results, and prove that they can track the moving object on real-time as shown in experiment results.