Camera calibration by using fringe patterns and 2D phase-difference pulse detection

Camera calibration is the most essential and usually the first step in computer vision applications. The results highly depend on the accuracy of the feature extraction. Conventional feature extraction methods suffer from perspective and lens distortion. In this paper, a novel feature extraction method is proposed by using fringe patterns groups as calibration target. Each group comprises six sinusoidal, in which, three are used for calculating vertical phases and the other three for horizontal phases. A three-step phase shift algorithm is used for wrapped phase calculation. Then, feature points are detected with a 2D phase-difference pulse detection method and refinement is done by simple interpolation. Finally, camera calibration is done by using these features as control points, experimental results indicated the proposed method accurate and robust.