A four-step camera calibration procedure with implicit image correction

TLDR

Geometric camera calibration seeks to determine camera parameters mapping 3‑D reference points to 2‑D image coordinates, yet most work focuses on model fitting while the full calibration pipeline—including control point extraction, image correction, and associated errors—has received limited attention. This study proposes a four‑step calibration procedure that extends the conventional two‑step method. The procedure adds a distortion‑compensation step for circular features, applies an empirical inverse model to correct radial and tangential distortions, and uses a linear solver to estimate the inverse‑model parameters.

Abstract

In geometrical camera calibration the objective is to determine a set of camera parameters that describe the mapping between 3-D reference coordinates and 2-D image coordinates. Various methods for camera calibration can be found from the literature. However surprisingly little attention has been paid to the whole calibration procedure, i.e., control point extraction from images, model fitting, image correction, and errors originating in these stages. The main interest has been in model fitting, although the other stages are also important. In this paper we present a four-step calibration procedure that is an extension to the two-step method. There is an additional step to compensate for distortion caused by circular features, and a step for correcting the distorted image coordinates. The image correction is performed with an empirical inverse model that accurately compensates for radial and tangential distortions. Finally, a linear method for solving the parameters of the inverse model is presented.