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IMPLEMENTATION OF OBJECT TRACKING SYSTEM USING REGION FILTERING ALGORITHM BASED ON SIMULINK BLOCKSETS

Video tracking is the process of locating a moving object in time that is visualized by camera and are widely used in surveillance, animation and robotics Tracking describes the process of recording movement and translating that movement onto a digital model. The set of constraints that produce the most accurate tracking is the one that describes better the action performed. The key difficulty in video tracking is to associate target locations in consecutive video frames, especially when the objects are moving fast relative to the frame rate. Here, a video tracking system is been employed in which motion model describes how the image of the target might change for different possible motions of the object to track. The role of the tracking algorithm adopted for this system is to analyze the video frames to estimate the motion parameters. These parameters characterize the location of the target. In this research, three features are been extracted from each moving objects such as centroid, area, average luminance. Finally the similarity function is applied to tracking and the attempt proves that the chosen method has good performance under dynamic circumstances for real time tracking. Simulink is integrated with MATLAB to build a model for object tracking and data transfer is easily handled between the programs. The Simulink based customizable framework is designed for rapid simulation, implementation, and verification of video and image processing algorithms and systems. Keywords-Tracking; Optical flow; Thresholding; Simulink; Region filtering; motion parameter