Key Technology Of Trinocular Vision Measurement With High Manifestation Level

Visual measurement is widely used in precision measurement technology. With the extension and expansion of computer technology, visual measurement technique has also received more attention. The thesis has proposed a series of relevant key topics about trinocular vision measurement system based on the illumination of parallel light. The manifestation method and manifestation intensity of the cameras at each site could vary for the choice of parallel light as the source. Through the processing method of complementarity or difference fusion of the image differences obtained by multiple cameras, the manifestation intensity of the foreground could be highlighted and the background noises or the interference effect of the non-measurement object could be removed. It could be very useful to separate the foreground information from the back ground to improve the saturation and uniformity of the feature edges. So this method could achieve higher precision in characteristic morphology detection and coutour dimension measurement than traditional signal-camera system.The main contributions of the thesis include:1. A trinocular vision measurement system based on the illumination of parallel light is proposed and the design principles and significance are discussed. The hardware of the system is designed and built, mainly including light source system, video capture system, adjustable platform of multi-degree of freedom and etc. With the design of the optical parameters,mechanical structures and electrical control system of the parallel light, a light source system is developed. Additionally, a platform system is built up, which could make the devices flexibly rotate at horizontal plane, and move along the directions of three degrees of freedom.2. The algorithm for detecting matching feature points of images in the trinocuar vision system are studied. In order to obtain matching feature points in three images, we propose some intelligent detecting methods for the features of corner point, circle, ellipse feature, including automatic corner points detection algorithm based on harris principle, automatic circle features detection algorithm based on hough transformation principle, automatic ellipse features detection algorithms based on the combination of the harris and hough transformation principles. The influences of target deflection angle on corner extraction are analyzed through different experiment targets. The row,column straightness obtained from the center points of circle or ellipse features is used to judge the extraction accuracy of the detection algorithms. The methods of detecting ellipse features with Both of the circle feature detection algorithms and ellipse fitting algorithms are comparative analyzed.3. The image registration and the calibration technique of the system has been deeply analyzed. 2D image matching method based on feature points is used, and a calculation method of 2D projective transformation relationship based on DLT and Ransac is proposed. Experiments are designed to analyze the influence of Gauss noise and wild point pairs on precision and time complexity when the DLT and Ransac combined method is used. Moreover, the actual matching effect and precision of the calculation method are analyzed through experiments processing on different objects. The geometric models of the camera system are analyzed and three kinds of camera internal parameters calibration schemes are proposed. Combined with different objects, we analyze the influences of different calibrate condition on the accuracy and stability of camera internal parameters calculation.4. A image-fusion coefficient optimization method is proposed which is based on the judgment methods of both the contrast ratio of the sampling points and the grey region. The characteristics of image fusion results with different coefficients are analyzed. With different fusion schemes, information, including defects detection, micr-concave-convex or fluctuant changes on the surface of workpiece, to be detected. The metal workpiece and gauge block are used as targets separately. It is discussed that the trinocuar vision system is much better in the measurement of contour dimension than the single vision system. In order to achieve the separation of the different information( such as the inner,outer edge and defect edge ), we proposed an classified information extraction method based on Radon, which is a one-dimensional directionally projection method. With the obtained positions of the different classified information, we could separate them from the image to conveniently analyze the contour dimensions for each information.5. The trinocuar vision imaging effect of the high diffusion target is analyzed through experiments of two high diffusion targets. And three-image fusion strategy based on serial image difference is proposed. Comparing the contrast ratio trend of the sample point in two targets, the different diffusion effects of these two targets can be understood. Then a judgment method is proposed about the reflection,diffusion effect of different material.