An Approach To Moving Object Tracking In Image Sequence

Detection and tracking of moving object in image sequence is an important area in the domain of digital image processing, pattern recognition and computer vision. Its applications include that robot navigation, security surveillance, medical image analysis and virtual reality.For a visual tracking system, the core includes two parts: one part is moving object detection and extraction, and the other is moving object tracking. Moving object extraction is the most important part. With incorrectly extracted or half-baked object, it may seriously affect the tracking operation, even can not track the object. For moving object detection, three methods which included"differential between adjacent frames","background subtraction"and"optical flow", are discussed. Through comparison and analysis, the merits, weaknesses and application field of each method are concluded. Image segmentation is an important step of object extraction. The object extraction is directly affected by the quality of image segmentation. In this paper, a"Two-dimensional OTSU-GA Adaptive Thresholding Segmentation Algorithm"is proposed. This Algorithm make Genetic Algorithm combine with Two-dimensional OTSU threshold Algorithm. It can make calculation faster by GA's capacity of searching the best answer. This algorithm improves the efficient of Image Segmentation.In this paper, nonparametric density estimation which is base of mean shift iteration is formulized thoroughly. The derivation of mean shift procedure as well as the strict proof of its convergence is given. On the object tracking research, the CamShift algorithm which means Continuous Adaptive Mean-Shift is mainly discussed. While Camshift is a tracking method based on the object's color character, and it is widely used for the parameter-less and fast calculation. CamShift algorithm works well in the simple background, but not in the complicated background. So the CamShift algorithm combined with Kalman filter is proposed in my paper. Kalman filter is used to forecast possible position of target, then Camshift search the real position near the possible position. The algorithm has good effect to moving target in the complicated background, and can deal well with simple occlution. The results proved that the algorithm is robust and practical.