Research On Key Issues Of Computer Vision System

Computer vision technologies have been widely used in industries, medical, aerospace and other fields, based on concluding the state of the art and future trends in the field of computer vision system, this dissertation systematically studied issues on camera calibration, image registration, visual tracking and visual measurement in-depth, and applied the theoretical research results to the corresponding computer vision tasks, which verify the feasibilities of the proposed algorithms.(1) The camera calibration issue is studied for non-ideal circumstances when the calibration object image clarity is not sufficient. Firstly the basic principles of planar-based two-step calibration algorithm are analyzed, then the image distortion measurement calculation method is given for measuring error of the proposed calibration algorithm, The calibration problem under non-ideal conditions is transformed into the optimization problem of the main control points, ultimately the particle swarm search strategy is utilized to accomplish the optimization process. Experimental results validate the effectiveness of the proposed algorithm, while the method is used in chapter 4 for image distortion correction part in the visual tracking task, demonstrates its practical value of the algorithm.(2)Image registration problem is studied for a class of non-constant amplitude image transformation model. Through the introduction of the amplitude difference coefficient describing the image gray level variation, the non-constant amplitude image transformation model is established. For non-constant amplitude translation model, the linear relationship between one zeros of the extended difference function and 1D translation is proved, and the extended difference function based image registration method is proposed. Experimental results show that the method is applicable to variant gray level images with good noise robustness and low complexity. For the non-constant amplitude rotation model, it is proved that Radon transform vectors can be taken as image feature for matching, and then a registration method is proposed based on Radon transform vectors matching, which utilizing multi scale searching strategy to search for the rotation angle. For non-constant amplitude rigid body transformation model, it is proved that the angular difference function and radial difference function can be used to solve the image rotation angle and scaling factor, and then a registration method is proposed based on the angular difference function and radial difference function. Simulation results show that the algorithm can effectively reduce the computing complexity, while achieving same accuracy with classic phase-correlation based method. The registration methods are verified effectively for vision tasks in Chapter 4 and Chapter 5.(3)Visual tracking issue is studied. For monocular visual tracking issue, an improved mean-shift tracking algorithm is proposed, using rigid-body model based image registration method to align images in tracking window, in this way establishes an auto-updating mechanism for tracking model. The method resolves the target missing problem resulting from similar color between foreground and background, target scaling changes, and target appears changes. For binocular tracking issue, a global view tracking algorithm is proposed based on image mosaicing technology. Experimental results show that the algorithm is effective.(4)The non-cooperative target vision pose measurement issue is studied, a two-stage non-cooperative target position and attitude measurement method is proposed, using motion stereo vision measurement technology to transform non-cooperative target into cooperative target, after that, P3P pose measurement method is used to estimate non-cooperative target position and attitude parameters. Motion stereo vision measurement technology utilizes monocular camera to simulate binocular stereo visual system to measure the target's features geometry size, and then to determine geometric structure of features, as the cooperation of non-cooperative targets. This method has been successfully applied to the space rendezvous and docking simulation system as visual measurement subsystem, the experiment results validate the feasibility of the proposed method.