Research On Several Key Technologies Of Handheld Coordinate Measuring System

Optical surface scanning technology has been widely used in industrial of onlinedetection, aerospace,engineering machinery,medical measurement. However, most of theexisting optical surface scanning technology can only measure parts of visible surface.Handheld three coordinate measurement is increasingly important in measuring shadingsurface of body parts and shell parts, such as complex inner cavity surface, the deephole,groove. The processing and manufacturing precision of these hidden shape affect theassembly quality between the mechanical parts directly, which will affect the useperformance and life of the component. In order to meet the increasing demand ofindustrial measuring, some related research of the handheld three coordinate measuringsystem has been carried on in this paper. This paper make some key techniques researchof the handheld three coordinate measuring system.Which include feature point imagerecognition algorithm based on mathematical morphology, feature point matchingalgorithm, system calibration.Feature point image recognition is very important for calculating the coordinates inthe measuring system. So an algorithm of feature point image recognition based onmathematical morphology is proposed for feature point image recognition. The methodwill apply the idea of mathematical morphology to image processing technology, whichmakes the target image and the background image can be segmentation effective, so as toidentify the feature points and extract digital image which only include the feature pointsquickly.Achieve the correct match to the corresponding points of the image in two camera isimportant for the light pen calibration. After identifying the extracted image feature points,each feature points need to be marked in order to ensure correct matching of the featurepoints in two cameras. This paper proposed a effective algorithm to match feature pointsbetween the left and right camera. Marked the feature points by the distance and therelative position relationship between the feature points，the feature points are marked areso that the two cameras can achieve proper matching feature points. Camera calibration and light pen calibration are included in system calibration, theaccuracy of the system calibration can affect the accuracy and the stability of themeasurement. For this reason，we choose a camera calibration method based on a2Dtarget. The calibration includes the calibration of the internal parameters of each cameraand the external parameters between two cameras. After the calibration of the internaland external parameters of the camera, the position and orientation relationship betweenthe two cameras are optimized. Then the world coordinate system is fixed on one of thecamera, to establish the object equation between the two cameras by the polar constraint,get two cameras precise position and orientation relations by optimizing the objectivesequation, the translation vector of the final scale factor correction, and the calibratedtranslation vector has to be revised to remove the scaling factor.Light pen calibration is the key to calculating the3d data for visual measurement. Alight pen self-calibration algorithm based on the same position of the probe has beenproposed. Fixed probe on a fixed location, change posture of the pen by rotating it,shooting the pen‘s posture in the image of N, To establish a transformation relationshipbetween camera coordinate system and the light pen coordinates, solve the rotation matrixby the singular value decomposition and translation vector, established equation underrigid transformation between the camera coordinate system and the light pen coordinatesof feature point, calculate the3d coordinates of the center of the probe in the light pencoordinates least squares.