Design of an Auto-Guiding System with Machine Vision and the Gaussian-Fitting Method

The upgrade and development of the auto-guiding system of the Lijiang 2.4m optical telescope need to incorporate accurate calculations of positions of stars in CCD images. Based on studying the available methods of stellar positioning, this paper gives a prescript of detecting edges of stellar images based on the Canny method with machine vision in conjunction with the method of recognizing stellar profiles with ellipse fitting. We subsequently use the 2-D Gaussian fitting to derive the stellar positions.We have studied the parameter-tuning method to estimate the sky brightness, the threshold, and the boundary coefficients required for fitting. The method is put into an efficient program of auto-guiding. In addition, we have developed a software under the Linux for a high-speed auto-guiding system. Results of our software agree well with those from the 2-D Gaussian fitting provided by the IRAF software. The drifts of the stellar positions calculated with the system from the images in adjacent time steps of the same sly survey further show the validity of the algorithm.