Non-contact 2D(3D) Measurement Technology Based On Machine Vision

In this paper modern optical test technique, computer technique and photoelectric technique are combined and micro-size detection based on the CCD matrix, imaging objective and computer is researched. The detection system images the measured workpiece by the CCD camera, the analog signal is transferred to the digital signal by the A/D converter on the image collector, the digital signal is stored in the memory and the workpiece image is processed by the compiled program. The paper solves the key technologies of non-linearity smooth, the threshold value selection and edge abstraction. the edge contour curve of workpiece can be precisely determined with the method of the edge contour tracking to obtain the edge contour image of workpiece. The system carried out experiments and explained the program ideas with the example of the nanoscale workpiece, circular workpiece and rectangle workpiece. It's easy to realize 2-D high accuracy, non-contact, real time and automatic measurement. The system has a simple structure and can be easily operated without the strict requests for environment.In this paper non-contact automatic measurement of three dimension is researched based on non-contact automatic measurement of two-dimension and binocular stereo vision technology. The paper studies the camera calibration, feature extraction and feature stereo matching of binocular stereo vision technology in detail.In the part of camera calibration, improved algorithm of Tsai-two-step method is proposed to achieve the binocular vision camera calibration. The paper researched the camera calibration algorithm based on the stereovision 3-D measurement principles and carried out the calibration experiments by employing the RAC two-step calibration technology and Levenberg-Marquardt nonlinear optimal algorithm.In the part of feature extraction, the paper analyses the Harris corner extraction algorithm and SUSAN corner extraction algorithm and SIFT feature extraction algorithm. The three feature extraction algorithms of different pictures are compared and analyzed. Experimental results show that the extracted feature points of SIFT feature extraction algorithm are more than other methods and it's beneficial to realize the further stereo matching of the matched base unit. When the picture is revolved, the position and number of the detected feature points are hardly changed.In the part of stereo matching, the objective surfaces of full-visible and part-visible are feature matched respectively and the matching formulas are obtained. The Harris corner matching and SIFT matching algorithms are implemented and the matching results of the two methods are compared and analyzed. Experiment results show that the performance of the SIFT matching algorithm is better than that of the Harris algorithm.A software framework with clear logic and stable performance based on the image processing library function OpenCV in the Visual C++ development platform is constructed. The system measurement demand is satisfied. In the developed experiments system,3-D measurement experiments are carried out with the examples of schoolbag and vase and performed the measurement tasks.