scholarly journals Detection of concentric circles for camera calibration

2005 ◽  
Author(s):  
Guang Jiang ◽  
Long Quan
Keyword(s):  
Camera Calibration ◽  
Concentric Circles

The location and identification of concentric circles in automatic camera calibration

2013 ◽  
Vol 54 ◽  
pp. 185-190 ◽  
Author(s):  
Xinyu Chen ◽  
Ying Hu ◽  
Zi Ma ◽  
Shuanghe Yu ◽  
Yuqing Chen
Keyword(s):  
Camera Calibration ◽  
Concentric Circles ◽  
Automatic Camera Calibration

Enhanced Camera Calibration for Machine Vision using OpenCV

2014 ◽  
Vol 3 (3) ◽  
pp. 136 ◽  
Author(s):  
Shubham Rohan Asthana
Keyword(s):  
Machine Vision ◽  
Camera Calibration ◽  
Calibration Procedure ◽  
Robot Hand ◽  
Grid Pattern ◽  
World Model ◽  
Hand Eye Coordination ◽  
Concentric Circles ◽  
Calibration Techniques ◽  
Good Calibration

In several machine vision applications, a fundamental step is to precisely determine the relation between the image of the object and its physical dimension by performing a calibration process. The aim is to devise an enhanced mechanism for camera calibration in order to improve the already existing methods in OpenCV. A good calibration is important when we need to reconstruct a world model or interact with the world as in case of robot, hand-eye coordination. In order to meet the rising demands for higher accuracy various calibration techniques have been developed but they are unable in obtaining precise results. In this paper we propose an enhanced camera calibration procedure using a special grid pattern of concentric circles with special markers. The overall objective is to minimize the re-projection for good camera calibration.

Using concentric circles and wedge grating for camera calibration

2012 ◽  
Vol 51 (17) ◽  
pp. 3811 ◽  
Author(s):  
Junpeng Xue ◽  
Xianyu Su ◽  
Liqun Xiang ◽  
Wenjing Chen
Keyword(s):  
Camera Calibration ◽  
Concentric Circles

scholarly journals Method of Camera Calibration Using Concentric Circles and Lines through Their Centres

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Yue Zhao ◽  
Xuechun Wang ◽  
Fengli Yang
Keyword(s):  
Camera Calibration ◽  
Real World ◽  
Cross Ratio ◽  
Lens Distortion ◽  
Vanishing Point ◽  
Vanishing Points ◽  
Novel Method ◽  
Ideal Points ◽  
Concentric Circles ◽  
The Ideal

A novel method for camera calibration is proposed based on an analysis of lens distortion in camera imaging. In the method, a line through the centre of concentric circles is used as a template in which orthogonal directions can be determined from an angle of circumference that corresponds to a diameter. By using three lines through the centre of concentric circles, based on the invariance of the cross-ratio, an image at the centre of the concentric circles can be used to obtain the vanishing point. The intrinsic parameters of the camera can be computed based on the constraints of the orthogonal vanishing points and the imaged absolute conic. The lens distortion causes points in the template to have a position offset. In the proposed method, we optimize the positions of the distortion points such that they gradually approach those of the ideal points. The simulated and real-world experiments demonstrate that the proposed method is efficient and feasible.

EFFECTIVE AND AUTOMATIC CALIBRATION USING CONCENTRIC CIRCLES

2008 ◽  
Vol 22 (07) ◽  
pp. 1379-1401 ◽  
Author(s):  
LIANG WANG ◽  
HONGXUN YAO ◽  
H. D. CHENG
Keyword(s):  
Camera Calibration ◽  
Test Pattern ◽  
Geometric Constraints ◽  
Automatic Calibration ◽  
Entire Process ◽  
Concentric Circles ◽  
Metric Measurement ◽  
Calibration Approach

In this paper, we present an effective, flexible and completely automated camera calibration approach using only one pair of concentric circles. This approach utilizes the characteristics of concentric circles' tangent lines to locate the center of these circles, and finds the geometric constraints for calibration based on the orthogonality formed by a point on the circle and the two intersected points of the circle with the line through the center of the circle. The entire process requires no conic equation fitting and no metric measurement of the test pattern, which is very flexible to implement.

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