基于双目视觉的齿轮倒角检测方法的研究
[Abstract]:Binocular stereo vision measurement system is to simulate the functions of human visual system to obtain the depth information of the measured object in the scene and restore the three-dimensional information of the measured object in the scene. Binocular stereo camera can realize non-contact measurement by collecting image information of gear chamfering angle. Compared with mechanical contact measurement, non-contact measurement has the advantages of high efficiency and no damage to the object under test. Therefore, the research of bevel angle measurement based on binocular vision gear has important theoretical significance and practical value. Based on the principle of binocular stereo vision, this paper studies the three-dimensional measurement method of gear chamfering by moving a single camera with a mechanical device. The main contents of this paper are as follows: (1) using two different cameras, the camera imaging model is established, and the influence of camera distortion in the imaging process is considered. The internal parameters of two cameras and the external parameters between two cameras are obtained by using the calibration method of Zhang Zhengyou. The results of calibration of two camera parameters are used for polar line correction. The binocular stereo vision model is transformed into the ideal parallel binocular vision. (2) the binocular stereo vision measurement method based on the mobile monocular camera is to carry a single camera with a mobile platform to realize the binocular stereo of two cameras. Visual measurement function The measurement of parallel binocular stereo vision is realized by using mechanical device instead of software calculation. The experiments of this method include the stability of the experimental device, the moving center distance of the camera and the measuring experiment. Through the analysis of experimental data, the feasibility of the measurement method is verified. (3) for the stereo matching model based on feature points, this paper studies several edge detection algorithms. According to the actual situation, the corresponding edge extraction algorithm is proposed to fit the edges and solve the feature points. The depth information of the measured object and the spatial coordinates of the feature point are obtained by matching the feature points, and then the measurement requirements are achieved.
【学位授予单位】:天津科技大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:TG86
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