Research On Structured Light 3D Measurement Using Inverse Camera

Three-dimensional(3D)measurement with structured light projection is able to provide complete and accurate depth information of the measured object and has been increasingly widely used in many fields,such as industrial detection,medical diagnosis,culture,education,studio entertainment,and so on,which benefits from its advantages of non-contact,high precision,high speed,and high degree of automat,etc.Due to the effect of limited fields of view,the blind spot of the optical projection code,complex surface geometry of the measured object,it is often difficult to achieve overall measurement of the measured object surface by single measurement.It has to divide the surface of the measured object and make multiple measurements from different perspectives.In order to further improve the precision and efficiency of structured light measurement,a reverse camera is installed on a structured light system as an auxiliary devices.When the single measurement of local 3D data is operated,the reverse camera observes a global oriented target.In the case of the relative pose between the reverse camera and the structured light measurement is calibrated,the pose of the structured light measurement relative to the global oriented target is obtained.The reverse camera is used as the pose transfer medium,all local 3D data are unified in a global frame defined with the oriented target,to achieve the whole large scale and high precision 3D measurement.The main research content of this dissertation is as follows.1.3D measurement technology based on structured light projection has been researched,including camera imaging model,Zhang's calibration method,grating projection and structured light encoding and decoding methods.2.This dissertation presents a multiple cameras calibration method based on laser rangefinder and planar target for multiple cameras with non-overlapping fields of view.The method fixes the laser rangefinder on the target,firstly according to the co-linearity of the laser spots and the measurement parameter,compute the external parameters between the luminous point and the target.Then,with the laser rangefinder's help,fields of view of neighboring cameras are connected,thus the extrinsic parameters of cameras can be calculated.The experiment results show that the presented method is feasible.3.It is presented that a projector calibration method based on radial basis function neural network.Fundamental corresponding relation is built between projector image and camera image based on projective transformation theory.After that the corresponding relationship is established by using RBF neural network to compensate errors.Thus the corresponding coordinates of the 3D calibration point in the projector image are determined from the image coordinates in the camera image.Finally,system calibration is accomplished.4.Building the relation between 3D space object and image,depth information of the measured object is obtained through image processing,feature extraction,point cloud match.Research and experimental results show that the proposed system calibration method can form an easy to operating,accurate and effective 3D large scale and high precision structured light projection system.