scholarly journals Depth-Dependent High Distortion Lens Calibration

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3695 ◽  
Author(s):  
Carlos Ricolfe-Viala ◽  
Alicia Esparza
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Complex Problem ◽  
Lens Distortion ◽  
Lens Model ◽  
Distortion Model ◽  
Calibration Methods ◽  
Depth Dependency ◽  
Division Model

Accurate correction of high distorted images is a very complex problem. Several lens distortion models exist that are adjusted using different techniques. Usually, regardless of the chosen model, a unique distortion model is adjusted to undistort images and the camera-calibration template distance is not considered. Several authors have presented the depth dependency of lens distortion but none of them have treated it with highly distorted images. This paper presents an analysis of the distortion depth dependency in strongly distorted images. The division model that is able to represent high distortion with only one parameter is modified to represent a depth-dependent high distortion lens model. The proposed calibration method obtains more accurate results when compared to existing calibration methods.

Camera Calibration Method Based on Circle Plane Board

2013 ◽  
Vol 475-476 ◽  
pp. 184-187
Author(s):  
Wen Guo Li ◽  
Shao Jun Duan
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Lens Distortion ◽  
Edge Extraction ◽  
Circle Plane ◽  
Circle Centre ◽  
Extraction Algorithm ◽  
Calibration Algorithm ◽  
Characteristic Points ◽  
Distortion Parameters

We present a camera calibration method based on circle plane board. The centres of circles on plane are regarded as the characteristic points, which are used to implement camera calibration. The proposed calibration is more accurate than many previous calibration algorithm because of the merit of the coordinate of circle centre being obtained from thousand of of edge pionts of ellipse, which is very reliable to image noise caused by edge extraction algorithm. Experiments shows the proposed algorithm can obtain high precise inner parameters, and lens distortion parameters.

scholarly journals Extrinsic Parameters Calibration Method of Cameras with Non-Overlapping Fields of View in Airborne Remote Sensing

2018 ◽  
Vol 10 (8) ◽  
pp. 1298 ◽  
Author(s):  
Lei Yin ◽  
Xiangjun Wang ◽  
Yubo Ni ◽  
Kai Zhou ◽  
Jilong Zhang
Keyword(s):  
Remote Sensing ◽  
Camera Calibration ◽  
Calibration Method ◽  
Optimization Method ◽  
Airborne Remote Sensing ◽  
Camera System ◽  
Translation Error ◽  
Camera Systems ◽  
Calibration Methods ◽  
Extrinsic Parameters

Multi-camera systems are widely used in the fields of airborne remote sensing and unmanned aerial vehicle imaging. The measurement precision of these systems depends on the accuracy of the extrinsic parameters. Therefore, it is important to accurately calibrate the extrinsic parameters between the onboard cameras. Unlike conventional multi-camera calibration methods with a common field of view (FOV), multi-camera calibration without overlapping FOVs has certain difficulties. In this paper, we propose a calibration method for a multi-camera system without common FOVs, which is used on aero photogrammetry. First, the extrinsic parameters of any two cameras in a multi-camera system is calibrated, and the extrinsic matrix is optimized by the re-projection error. Then, the extrinsic parameters of each camera are unified to the system reference coordinate system by using the global optimization method. A simulation experiment and a physical verification experiment are designed for the theoretical arithmetic. The experimental results show that this method is operable. The rotation error angle of the camera’s extrinsic parameters is less than 0.001rad and the translation error is less than 0.08 mm.

scholarly journals Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4643
Author(s):  
Sang Jun Lee ◽  
Jeawoo Lee ◽  
Wonju Lee ◽  
Cheolhun Jang
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Image Features ◽  
Intelligent Vehicles ◽  
Point Problem ◽  
Reconstruction Method ◽  
Calibration Methods ◽  
The World ◽  
Extrinsic Parameters ◽  
Automatic Camera Calibration

In intelligent vehicles, extrinsic camera calibration is preferable to be conducted on a regular basis to deal with unpredictable mechanical changes or variations on weight load distribution. Specifically, high-precision extrinsic parameters between the camera coordinate and the world coordinate are essential to implement high-level functions in intelligent vehicles such as distance estimation and lane departure warning. However, conventional calibration methods, which solve a Perspective-n-Point problem, require laborious work to measure the positions of 3D points in the world coordinate. To reduce this inconvenience, this paper proposes an automatic camera calibration method based on 3D reconstruction. The main contribution of this paper is a novel reconstruction method to recover 3D points on planes perpendicular to the ground. The proposed method jointly optimizes reprojection errors of image features projected from multiple planar surfaces, and finally, it significantly reduces errors in camera extrinsic parameters. Experiments were conducted in synthetic simulation and real calibration environments to demonstrate the effectiveness of the proposed method.

scholarly journals DoF-Dependent and Equal-Partition Based Lens Distortion Modeling and Calibration Method for Close-Range Photogrammetry

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5934
Author(s):  
Xiao Li ◽  
Wei Li ◽  
Xin’an Yuan ◽  
Xiaokang Yin ◽  
Xin Ma
Keyword(s):  
Optical Axis ◽  
Focal Length ◽  
Calibration Method ◽  
Depth Of Field ◽  
Model Parameters ◽  
Lens Distortion ◽  
Camera Model ◽  
Distortion Model ◽  
Manual Adjustment ◽  
Close Range

Lens distortion is closely related to the spatial position of depth of field (DoF), especially in close-range photography. The accurate characterization and precise calibration of DoF-dependent distortion are very important to improve the accuracy of close-range vision measurements. In this paper, to meet the need of short-distance and small-focal-length photography, a DoF-dependent and equal-partition based lens distortion modeling and calibration method is proposed. Firstly, considering the direction along the optical axis, a DoF-dependent yet focusing-state-independent distortion model is proposed. By this method, manual adjustment of the focus and zoom rings is avoided, thus eliminating human errors. Secondly, considering the direction perpendicular to the optical axis, to solve the problem of insufficient distortion representations caused by using only one set of coefficients, a 2D-to-3D equal-increment partitioning method for lens distortion is proposed. Accurate characterization of DoF-dependent distortion is thus realized by fusing the distortion partitioning method and the DoF distortion model. Lastly, a calibration control field is designed. After extracting line segments within a partition, the de-coupling calibration of distortion parameters and other camera model parameters is realized. Experiment results shows that the maximum/average projection and angular reconstruction errors of equal-increment partition based DoF distortion model are 0.11 pixels/0.05 pixels and 0.013°/0.011°, respectively. This demonstrates the validity of the lens distortion model and calibration method proposed in this paper.

scholarly journals A Fast Calibration Method for Photonic Mixer Device Solid-State Array Lidars

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 822 ◽  
Author(s):  
Yayu Zhai ◽  
Ping Song ◽  
Xiaoxiao Chen
Keyword(s):  
Solid State ◽  
High Reliability ◽  
Calibration Method ◽  
Black Box ◽  
Oxide Semiconductor ◽  
Lens Distortion ◽  
Research Attention ◽  
Adaptive Interpolation ◽  
Calibration Methods ◽  
Calibration Device

The photonic mixer device (PMD) solid-state array lidar, as a three-dimensional imaging technology, has attracted research attention in recent years because of its low cost, high frame rate, and high reliability. To address the disadvantages of traditional PMD solid-state array lidar calibration methods, including low calibration efficiency and accuracy, and serious human error factors, this paper first proposes a calibration method for an array complementary metal–oxide–semiconductor photodetector using a black-box calibration device and an electrical analog delay method; it then proposes a modular lens distortion correction method based on checkerboard calibration and pixel point adaptive interpolation optimization. Specifically, the ranging error source is analyzed based on the PMD solid-state array lidar imaging mechanism; the black-box calibration device is specifically designed for the calibration requirements of anti-ambient light and an echo reflection route; a dynamic distance simulation system integrating the laser emission unit, laser receiving unit, and delay control unit is designed to calibrate the photodetector echo demodulation; the checkerboard calibration method is used to correct external lens distortion in grayscale mode; and the pixel adaptive interpolation strategy is used to reduce distortion of distance images. Through analysis of the calibration process and results, the proposed method effectively reduces the calibration scene requirements and human factors, meets the needs of different users of the lens, and improves both calibration efficiency and measurement accuracy.

A Novel Camera Calibration Method Based on Circle Array Target

2012 ◽  
Vol 472-475 ◽  
pp. 968-973
Author(s):  
Hong Ru Wang ◽  
Wen Ding
Keyword(s):  
Camera Calibration ◽  
Visual Inspection ◽  
Assembly Line ◽  
Calibration Method ◽  
Lens Distortion ◽  
Feature Points ◽  
Improved Genetic Algorithm ◽  
Improve Accuracy ◽  
Two Stages ◽  
The Given

To improve accuracy of computer visual inspection in keyboard automatic assembly line, a new two-stage camera calibration method was presented. 2D circle array was used as calibration plate, and centers of the circles were taken as feature points. And feature point coordinates were extracted without human interference. The proposed camera calibration method was divided into two stages. First, lens distortion was neglected, internal and external parameters of the camera were obtained by modified camera calibration toolbox for MATLAB. Then, lens distortion was taken into account, and improved genetic algorithm (GA) was adopted to optimize camera parameters gotten in the first stage. Experiment results indicate the proposed method is feasible, and can meet with requirements of the given application.

A New Binocular Camera Calibration Method Based on an Improved Genetic Algorithm

2011 ◽  
Vol 411 ◽  
pp. 602-608 ◽  
Author(s):  
Xiang Kui Jiang
Keyword(s):  
Genetic Algorithm ◽  
Camera Calibration ◽  
Calibration Method ◽  
Improved Genetic Algorithm ◽  
Linear Calibration ◽  
Calibration Methods ◽  
Calibration Accuracy ◽  
Encoding Method ◽  
The One ◽  
Crossover And Mutation

In this paper,an improved genetic algorithm was proposed,which is applicable to binocular camera calibration. On the one hand, conventional encoding method is improved so that variable search interval can be adjusted adaptively. On the other hand, crossover and mutation probability is varied by using superiority inheritance principle to avoid premature question. Experimental results show that the proposed method has a higher calibration accuracy and better robustness, compared to those of non-linear calibration methods. The proposed method is able to improve the performance of global optimization effectively.

Investigation of Factors Influencing Calibration Accuracy of Camera

2013 ◽  
Vol 712-715 ◽  
pp. 2331-2335
Author(s):  
Jian Hua Wang ◽  
Yu Ping Wu ◽  
Zhao Yang
Keyword(s):  
Camera Calibration ◽  
Control Point ◽  
Calibration Method ◽  
Manufacturing Error ◽  
Manufacturing Tolerance ◽  
Factors Influencing ◽  
Calibration Methods ◽  
Machine Vision Application ◽  
Calibration Accuracy ◽  
Vision Application

Camera calibration is the basis of vision-based 3D measurement. While many calibration methods have been proposed, the problem encountered in the practice of camera calibration is how to get accurate calibration parameters, which is seldom involved in references. This paper is focused on investigation of main factors influencing calibration accuracy, including manufacturing error of calibration rig, extracting error of control point and their combination. Based on the popular calibration method, simulation experiments are conducted at different error level, and the results show that the extracting error of control point has greater effect on calibration accuracy than manufacturing error of calibration rig. The manufacturing tolerance of calibration rig and extracting tolerance of control point is suggested to satisfy usual machine vision application.

The Application Research of Robot Vision Target Positioning Based on Static Camera Calibration

2013 ◽  
Vol 712-715 ◽  
pp. 2378-2384
Author(s):  
Jiang Yan Yin
Keyword(s):  
Camera Calibration ◽  
Vision System ◽  
Research Work ◽  
Robot Vision ◽  
Target Position ◽  
Calibration Method ◽  
Lens Distortion ◽  
Application Research ◽  
Distortion Coefficient ◽  
Key Techniques

Target precise positioning by vision system is one of key techniques in robot vision system. In target positioning and selection with robot vision technique, the camera lens distortion must be calibrated. In this paper, a calibration method based on segment slope is used to calibrate the camera and the radial lens distortion coefficient is obtained. The distortion coefficient is used in calculating target position coordinates, and the robot end-exceutor is led to position the target with the use of the coordinates. The experimental results show the effectiveness of the research work. Keywords:robot vision;camera calibration;radial distortion;target positioning

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