Camera calibration method based on ellipse eccentricity compensation

Abstract In the field of visual measurement, camera calibration is the first step and an important step in determining the accuracy of the measurement. Achieving rapid and accurate camera calibration has been a significant focus of research among scholars. Therefore, a high-precision camera calibration framework based on ellipse eccentricity compensation is proposed. In the first step, the Canny algorithm is used to detect ellipse edges. In the second step, a high-precision fitting of the ellipse is accomplished by a weighted fitting method. In the third step, the initial calibration parameters are calculated by using the coordinates of the elliptical center. Subsequently, the eccentricity deviation of the ellipse is compensated based on the initial calibration parameters. The updated coordinates are then used to recalculate the calibration parameters. This iterative process is repeated using an improved swarm intelligence optimization algorithm until the error is below the threshold or the number of iterations is reached. Simulations and experiments are used to verify the proposed method. The results show that the proposed method has high accuracy and stability, and can be widely used in engineering.