CAMERA CALIBRATION USING ADAPTIVE SEGMENTATION AND ELLIPSE FITTING FOR LOCALIZING CONTROL POINTS

This paper presents a novel camera calibration method using a circular calibration pattern. The disadvantages and issues with existing state-of-the-art methods are discussed and are overcome in this work. In the proposed iterative method, the captured images of the circular pattern are undistorted and projected onto a fronto parallel plane. The control points are localized in this fronto parallel plane using a novel approach for more accurately localizing the control points in the images based on adaptive segmentation and ellipse fitting. The localized control points are then projected to their original planes using estimated camera calibration parameters that are refined by minimizing the reprojection error. Simulation results are presented to illustrate the performance of the proposed scheme. These results show that the proposed method reduces the error by up to 57% as compared to the state-of-the-art for high-resolution images, and that the proposed scheme is more robust to blur in the imaged calibration pattern.