In an automatic lensometer based on Hartmann's method, the spot position received by the photoelectric detector is key for measuring diopter. Inaccurate extraction of the spot center can lead to large errors in diopter measurement. This study analyzes the impact of spot offset on diopter error and examines the correlation between spot offset and diopter error, to propose a random circle detection and fitness evaluation method for spot localization based on random sample consensus (RANSAC). First, the spot is preprocessed, including bicubic interpolation, binarization, and Canny edge detection, which improves the accuracy and completeness of the integrity of edge information. Then, using the radial scanning method, starting from the center of the rough localization circle of the spot, edge points are uniformly collected, and three points are randomly selected to generate candidate circles. The circle with the highest fitness is output as the center of the spot. Compared with four traditional methods such as the least squares circle detection method, the proposed method can quickly and accurately locate the center of the spot, with a measurement accuracy of 0.242 pixel, which can effectively improve the accuracy of the refraction measurement by the automatic lensometer.