A robotic vision system has been designed and analyzed for real time tracking of maneuvering objects. Passive detection using live TV images provides the tracking signals derived from the video data. The calibration and orientation of two cameras is done by a bundle adjustment technique. The target location algorithm determines the centroid coordinates of the target in the image plane and relates it to the aim point in the object plane. The stereoscopic images provide the information, from which the range, r of the object can be determined. The azimuth, θ and elevation, ϕ of the target with respect to a certain origin are determined by correlating the x-y displacements of the centroid in the image plane with the angular displacement of the target in the object plane. The servo drive signals for both the robot motion and the angular positioning of the cameras are derived from the image processing algorithm that keeps the centroid of the target image in the center of the frame and the target in line with the axis of the optical system. Hence, the spherical coordinates of the target are defined and updated with every TV frame. The time development of the centroid in successive TV frames represents the real time trajectory of the target path. A non-linear prediction technique keeps the target within the aim zone of the tracking system. In order to minimize the image processing time, i.e. kept within the demand of real time operation, one TV frame time, an image segmentation process is made to subtract nearly all redundant background details
['Khalid Khalid Al Khateeb', 'Mat Kamil Awang', 'Othman Omran Khalifa']
Intelligent auto tracking in 3D space by image processing