An automatic camera calibration method based on checkerboard

The traditional camera calibration methods faces many problems, such as the need for manual operation and high-quality images as well as the heavy time consumption. To solve these problems, this paper puts forward an adaptive extraction and matching algorithm for checkerboard inner-corners for camera calibration. Firstly, the coordinates of all corner points of the checkerboard were derived by the Harris algorithm. Then, the four vertices of the checkerboard were acquired in the image coordinate system based on polygonal convexity. After that, the coordinates of the inner-corner points of the checkerboard image were obtained against the judgement rules that distinguish inner-corner points from other points on that image. On this basis, the matching relationship was established between the inner-corner points of the checkerboard image in the image coordinate system and those in the checkerboard coordinate system. Finally, the theoretical modelling, judgement rules and a mature camera calibration model were integrated for automatic camera calibration experiments. The results show that the automatic camera calibration method based on the proposed algorithm consumed 75% less time than the Matlab toolbox and controlled the error within 0.3 pixels. This research provides a real-time, robust and accurate automatic camera calibration method for engineering applications.