Research On The Key Techniques And System Of Binocular Stereo Measurement Based On Random Illumination

3D profile measuring is a highly demanding technique for industrial applications, such as reverse engineering, product quality control and virtual reality. It can be widely used in aerospace manufacturing, automobile making, shipbuilding, machine-tool industries, biomedicine, die manufacturing, etc. Among the existing 3D measurement techniques, image-based methods have demonstrated its vitality and promising future for its characteristics of non-tactility, high precision, efficiency and practicability. One optical method based on instantaneous random illumination has been fully studied in this thesis, and so does the key techniques for binocular stereo measurement including image analysis, camera calibration, matching, reconstruction, registration, software & hardware implementation, etc. The thesis's main contributions are as follows.Binocular stereo measurement key techniques based on instantaneous random illumination have been researched. To acquire 3D point cloud data of a target object with low cost and simple setup, an instantaneous random illumination projection facility has been made to instantaneously project a random image pattern onto the object surface. Stereo images taken from two calibrated cameras with fixed geometry are matched and reconstructed for 3D point cloud acquisition. Since the stereo image pair is snapped simultaneously and instantaneously, the system is practicable for field measurement and moving objects'measurement because of its immunity to vibration of the object. In addition, since there are no strict constraints on light pattern projection such as distortion control, no raster movement mechanics and no cooling hardware, the structure of the projector and futher even the whole system can be compact and of low cost.Since the inputs of the binocular measurement are all images, image processing has been researched including contour detection and ellipse location. The outputs of the image processing algorithms serve as the input of afterwards camera calibration and image matching. Circular features are used as fiducial markers. Subpixel ellipse center detection and location algorithms based on least squares methods are analyzed. Since many kinds of fake features may exist in the real images, a fake ellipse removing algorithm is proposed. This ellipse extraction algorithm is robust and of high precision, and serves well as the input for the following stereo calibration and stereo registration algorithms.Camera model and binocular calibration have been researched. The measurement system's camera distortion model has been carefully selected based on many experiments'analyse, and a practicable 3-step stereo calibration algorithm is proposed. In this method, planar plate based calibration is adopted. A normal 2-step calibration process is adopted which is similar to other typical calibration methods, and a further optimization procedure is included which takes feature points'3D coordinates as parameters. And after that, real metrics are obtained by scaling with respect to known distance between two fixed points. Since 3D coordinates'errors are taken into consider, calibration could be done with good precision while calibration plates'can be easily made.Aiming at binocular stereo reconstruction, a stereo matching and reconstruction algorithm is proposed. During reconstruction and matching, image intensity and geometrical constraint information are taken into account. The least squares method is applied to iteratively resolve the affine parameters and 3D coordinates. Image grey level correction is done before the least squares resolvement for the sake of speed. And with the assumed continuity constraint, a region growing strategy has been adopted. It is demonstrated by experiments that our matching and reconstruction algorithm can acquire fairly good surface point cloud for normal usage.Aiming at the registration of point cloud data computed from different views, registration algorithm with global optimization based on circular features has been proposed. Since the coordinate system changes between different views, a registration algorithm for transforming these point cloud data is needed. Firstly, an adaptive relaxation algorithm with"adaptive some winners take all"strategy is proposed for feature based image registration; secondly, 3D registration for two views is performed based on the fact that the Euclidean distance between any two points remains unchanged in different views; and at last, global optimization is implemented for the final 3D registration. Experiments show that the registration algorithm can robustly transfrom different views'data to a universal coordinate system.A prototype binocular measurement system, namely RIMS (Random Illumination Measurement System) based on instantaneous random illumination is designed and made with above key algorithms and techniques. For the hardware, suitable cameras and lens are selected; an instantaneous random illumination projector is made for instantaneous random pattern projection; a circuit board is designed for synchronization of camera image capture and lamp flash. For the software, stereo calibration, image matching and 3D reconstruction, cloud polygonization and display algorithm et al. have all been coded, implemented and integrated with VC++ for the primary functionality of the system.The proposed algorithms and system functionalities have all been fully experimented and analyzed. It has been demonstrated that the representive target objects'surface point cloud can be obtained fairly well by the prototype system. Because of its characteristics of effectiveness and good precision, the solution proposed in this paper has great potential tobe widely used in diverse applications.