Lens Calibration Method Research Articles

Zoom lens calibration with zoom- and focus-related intrinsic parameters applied to bundle adjustment

A zoom lens is more flexible for photogrammetric measurements under diverse environments than a fixed lens. However, challenges in calibration of zoom-lens cameras preclude the wide use of zoom lenses in the field of close-range photogrammetry. Thus, a novel zoom lens calibration method is proposed in this study. In this method, instead of conducting modeling after monofocal calibrations, we summarize the empirical zoom/focus models of intrinsic parameters first and then incorporate these parameters into traditional collinearity equations to construct the fundamental mathematical model, i.e., collinearity equations with zoom- and focus-related intrinsic parameters. Similar to monofocal calibration, images taken at several combinations of zoom and focus settings are processed in a single self-calibration bundle adjustment. In the self-calibration bundle adjustment, three types of unknowns, namely, exterior orientation parameters, unknown space point coordinates, and model coefficients of the intrinsic parameters, are solved simultaneously. Experiments on three different digital cameras with zoom lenses support the feasibility of the proposed method, and their relative accuracies range from 1:4000 to 1:15,100. Furthermore, the nominal focal length written in the exchangeable image file header is found to lack reliability in experiments. Thereafter, the joint influence of zoom lens instability and zoom recording errors is further analyzed quantitatively. The analysis result is consistent with the experimental result and explains the reason why zoom lens calibration can never have the same accuracy as monofocal self-calibration.

Adaptive 3D sensing system based on variable magnification using stereo vision and structured light

In this paper, the design and implementation of a 3D sensing system with adjustable zoom based on stereo vision and structured light is discussed. The proposed system consists of a stereo camera with an illumination projector and zoom lenses to collect high-resolution data from a distant object. A calibration target suitable for zoom lens calibration is designed along with the development of a zoom lens calibration method for a stereo camera based on linear and non-linear models. The robust zoom lens control system, based on a precise automation hardware and image processing technique, is developed to produce high-quality images. Furthermore, normalized cross correlation (NCC), being robust with intensity offsets and contrast changes, is used for stereo matching of the coded images to generate the reconstruction results using a linear equation method. The integration of NCC with structured light and epipolar geometry for the proposed 3D sensing system further yields accurate 3D reconstruction results as demonstrated in the experimental results of this research. The complex relationship of the parameters of each camera on variable zoom is determined using optimal fitting. Linear interpolation is used to estimate calibration data at an arbitrary zoom setting to validate zoom lens calibration. The 3D reconstruction on variable zoom shows that higher lens magnification results in a more accurate 3D sensing system.

Calibration and correction of lens distortion for two-dimensional digital speckle correlation measurement

Lens distortion practically presents in optical imaging system using in two-dimensional digital speckle correlation measurement (2D-DSCM) system, and gives rise to additional errors in the displacement and strain measurement. Camera calibration procedure is performed to obtain the coefficients of radial distortion and tangential distortion. The corrected displacement fields can be calculated using the distortion coefficient. The influence of distortion on displacement and strain measurement errors in experiment is further discussed. The three-point bending test result shows that the camera lens calibration method can effectively eliminate the effect of lens distortion and improve displacement and strain measurement accuracy.

Improving coaxial measurements in laser welding by correcting distortions of a laser focus lens with a wide field of view

A compact, lightweight, and multifunctional head for robotic laser welding applications has been equipped with a camera to provide a real time image stream of the work piece for seam teaching, tracking, and inspection purposes [D. Iakovou, R. G. K. M. Aarts, and J. Meijer, “Integrated sensors for robotic laser welding,” in Proceedings of the Third International WLT Conference on Lasers in Manufacturing, Munich, Germany (AT-Fachverlag GmBH, Stuttgart, 2005), pp. 121–126; D. Iakovou, R. G. K. M. Aarts, and J. Meijer “Sensor integration for robotic laser welding processes,” (paper No. 2301), in Proceedings of the International Congress on Applications of Lasers and Electro-Optics (ICALEO), Miami, 2005 (unpublished)]. The camera uses part of the laser focusing optics. Research has been done to identify and correct for positioning errors introduced by the optical system. A robust camera and lens calibration method has been developed. Calibration and seam detection experiments have been performed and the results were used for seam tracking.

Lens calibration without pre-designated distortion model and corresponding points

A new lens calibration method which is suitable for all kinds of cameras is presented. Based on the linear feature in the image, this method does not require the determination of point correspondence between a scene and the image of the scene. By applying B-spline surface fitting, all kinds of lens distortion models can be simulated. The control points of B-spline surface are estimated iteratively to extract linear feature from the distorted image. Compared with traditional calibration method, which requires either corresponding point pairs or distortion model of lens, or both of them, this method has its unique advantage. Experimental results show the effectiveness of the method.

Geometric calibration of lens using B-spline surface fitting

A new lens calibration method which is suitable for all kinds of cameras is presented. Based on the global and local adjustable feature of B-spline surface, this method does not require the determination of distortion model of the camera lens. By applying B-spline surface fitting, all kinds of lens distortion models can be simulated. The control points of B-spline surface are estimated inversly from the feature points of detected lines. Then by moving the control points, straight line features in the image can be retrieved. Compared with traditional calibration method, this method has its unique advantage that need no corresponding points between image and scene. Experimental results show the effectiveness of the method.