Study On Edge Detection And The Camera Calibration Algorithm

Computer vision is an active and challenging research field, its research and application areas spread widely. Based on development of on-line and real time detection control system about ceramics, this dissertation is devoted to investigating some related techniques in computer vision, including edge detection,conventional calibration, self-calibration and so on.In computer stereo vision, the primary problem to be solved is the relations between the 3D points and 2D image points. So the camera calibration is the premise and the basic problem. There are conventional calibration and self-calibration algorithms in camera calibration techniques. Since the camera lens used in computer vision sustain a lot of nonlinear distortion, recent research efforts has been concentrated on the distortion correcting techniques. The optimization algorithms in conventional calibration field have shortcomings that the computing quantity is colossal. In order to improve it, Tsai two steps' s algorithm was developed in conventional camera calibration in this dissertation, and a calibration algorithm considering radial distortion. Compared with the ordinary optimization algorithm of calibration, this algorithm is simplier,less computational and of high accuracy.In the first chapter, we introduce briefly in computer vision and edge detection. And then the paper puts forward the concept of image processing,studies and analyzes ordinary methods about image processing, which include image smoothing, edge detection, binarization and so on. Some calibration methods are recommended in the third chapter. On the basis of these methods, an easy method for camera calibration and correction is studied by the mathematical model of camera by use of projective theory. In the fourth chapter, we give conclusions and some perspectives.