When measuring the diameter of circular parts under the illumination methods of ring light source and strip light source, the problems are usually produced, such as the chamfer features of parts are prone to wide edges in the images, the shadows on the boundaries of circles are appeared due to the influence of thickness, the efficiency of image processing is affected by the surface textures and scratches, and the high-resolution panoramic image of large-sized circular parts is acquired multiple times due to insufficient camera field of view. In this paper, a measurement method for large-size circular parts size based on improved SURF image stitching is proposed, and the high-precision measurement of parts size is realized by illumination optimization, image stitching and sub-pixel edge detection. Firstly, the illumination methods of the strip light source arranged at 45°, the combination of ring light source arranged vertically downward and strip light source arranged at 45° are proposed respectively, thus, the wide edges, shadows, textures and scratches in the images of parts are eliminated, which influence the measurement of parts size. Secondly, the SURF feature matching method is improved to locate overlapping regions of stitching images for coarse matching of feature points. Thirdly, the RANSAC algorithm is proposed for accurate matching of feature points, the image registration method is improved to expand the stitching images of parts to the same size and complement the missing background areas. Fourthly, the weighted average fusion algorithm is proposed to smooth the stitched image, and the high-resolution parts panoramic image is obtained. Finally, the least squares fitting of circles is improved to fit the edge circle in the image, and the actual diameter measurement value of circular parts is obtained through pixel size conversion. The experimental results show that the proposed method is more accurate than the traditional visual measurement method, and the relative error with the CMM measurement reference value is less than 0.044 4%.