Research On Key Technology Of Precision Measurement Based On Computer Vision Image

Computer vision image precision measurement has been researched further and applied widely abroad as well as popular at home. With the ratio of computer hardware and performance increasing, the relative technology developing, the character of flexibility, fast speed, non-contact, high precision and automatization, the computer vision image precision measurement application will become global. Based on image, the system scheme of the computer vision image precision measurement, the design of software and hardware, especially the key technologies of solving precision, speed, stability using software have been researched further. This paper analyzed the basic theory of computer vision image precision measurement, hardware selecting, software function module and inspection flow, deduced the measurement precision of relatively calibration. The possibility of realizing the high precision measurement has been proved. According the characteristic of computer vision measurement, the author researched the methods of color image converting to gray and presented judging rules of gray transform arithmetic. The judging functions of keeping the edge structure characteristic have been presented aiming to step edge and roof edge. The simple GAUSS filter or SUSAN filter will be used to removal the noise in the calipers scope according the characteristic of image quality and GAUSS noise. This paper presented the edge detection method based on knowledge,utilized the calipers technology and USAN rule of SUSAN arithmetic to locate edge to pixel precision with the knowledge. It will improve the edge locating precision, resist noise and improve the calculating speed. Combining the merits of SUSAN and Canny, this paper presented the method of edge detection based on SUSAN and Canny. The method has the better results of edge detection. The sub-pixel edge location technology using moment were studied further in this paper based on the 1-D ideal step edge. The paper presented that the locating precision of spatial moment relates the sampling interval, calculating counter and edge symmetry. The gray level moment edge locating can acquire no error estimate when we do not consider the noise and selecting the symmetry edge in two limit states (inter-pixel edge and intra-pixel edge). The author presented the method of sub-pixel edge locating based on back and forth difference and curve fitting. This method has the same locating precision as the gray level moment in the two limit states and has the better result at the other condition. This paper developed a plane rotundity gridding template to proofreading the lens distortion. Using this template we can calculate the lens distortion coefficients. The author presented the two steps calibration for the computer vision image precision measurement, calculating the coefficients of distortion in the lab, pixel value and test data in the scene. As there are only linear matrix calculation and geometry distortion proofreading, this method solved the problems between the speed and precision in computer vision calibration. This paper analyzed the auto-focus judging function and presented the mean-square judged-function weighted in condition on the basis of mean-square difference judge-function. Selecting the appropriate scope in the computer vision image precision measurement, it will be reach the good focus effect. The technology problems of realizing the precision measurement using computer vision have been solved basically when we use the image in focus, the high precision edge location and calibration technology, distortion proofreading, callipers and knowledge. It is possible that we will use the computer vision widely in industry. This has important significance to promote the application of vision test technology.