Checkerboard Corner Detection Based on Hough Transform and Circular Template

Aiming at resolving the issue of accuracy of the existing checkerboard corner detection algorithms, we propose a high-precision checkerboard corner detection algorithm based on Hough transform and circular template. First, we used the Hough transform to extract straight lines in an image, used the distribution features of the checkerboard lines to obtain the effective straight lines, and then obtained and roughly located the approximate corner points based on these lines. Second, we constructed a new circular template that is moved around the roughly located corner points to search for related points; we simultaneously obtained their image coordinates and observation distances. Finally, we solved more accurate corners, which should satisfy the minimum difference between the actual distances from related points and their observation distances. The experimental results reveal that the calibration error of the proposed method significantly reduces compared with the existing methods. When the illumination is not ideal, the proposed method can also realize accurate detection. This method provides a strong basis for the application of high-precision calibration of actual cameras.