scholarly journals A Camera Calibration Method with Large Oblique Angle Machine Vision

2018 ◽  
Vol 435 ◽  
pp. 012040
Author(s):  
Meng Chen ◽  
Yue Lei He ◽  
Pei Yi Gong ◽  
Zai Wei Li ◽  
Hong Yao Lu
Keyword(s):  
Machine Vision ◽  
Camera Calibration ◽  
Calibration Method ◽  
Oblique Angle

scholarly journals Design and Image Research of Tennis Line Examination Based on Machine Vision Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Liu Yan ◽  
Sun Xin
Keyword(s):  
Machine Vision ◽  
Camera Calibration ◽  
Recognition Accuracy ◽  
Calibration Method ◽  
Recognition Method ◽  
Systematic Analysis ◽  
High Recognition Accuracy ◽  
Intelligent Recognition ◽  
Region Growth ◽  
Design Experiments

In view of the intelligent demand of tennis line examination, this paper performs a systematic analysis on the intelligent recognition of tennis line examination. Then, a tennis line recognition method based on machine vision is proposed. In this paper, the color region of the image recognition region is divided based on the region growth, and the rough estimation of the court boundary is realized. In order to achieve the effect of camera calibration, a fast camera calibration method which can be used for a variety of court types is proposed. On the basis of camera calibration, a tennis line examination and segmentation system based on machine vision analysis is constructed, and the experimental results are verified by design experiments. The results show that the machine vision analysis-based intelligent segmentation system of tennis line examination has high recognition accuracy and can meet the actual needs of tennis line examination.

scholarly journals A Machine Vision Rapid Method to Determine the Ripeness Degree of Olive Lots

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2940
Author(s):  
Luciano Ortenzi ◽  
Simone Figorilli ◽  
Corrado Costa ◽  
Federico Pallottino ◽  
Simona Violino ◽  
...  
Keyword(s):  
Machine Vision ◽  
Nearest Neighbors ◽  
Calibration Method ◽  
Mobile App ◽  
Harvest Time ◽  
Automatic Assessment ◽  
K Nearest Neighbors ◽  
Olive Ripeness ◽  
Olive Ripening

The degree of olive maturation is a very important factor to consider at harvest time, as it influences the organoleptic quality of the final product, for both oil and table use. The Jaén index, evaluated by measuring the average coloring of olive fruits (peel and pulp), is currently considered to be one of the most indicative methods to determine the olive ripening stage, but it is a slow assay and its results are not objective. The aim of this work is to identify the ripeness degree of olive lots through a real-time, repeatable, and objective machine vision method, which uses RGB image analysis based on a k-nearest neighbors classification algorithm. To overcome different lighting scenarios, pictures were subjected to an automatic colorimetric calibration method—an advanced 3D algorithm using known values. To check the performance of the automatic machine vision method, a comparison was made with two visual operator image evaluations. For 10 images, the number of black, green, and purple olives was also visually evaluated by these two operators. The accuracy of the method was 60%. The system could be easily implemented in a specific mobile app developed for the automatic assessment of olive ripeness directly in the field, for advanced georeferenced data analysis.

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.

CCD Camera Calibration Technology Based on the Translation of Coordinate Measuring Machine

2014 ◽  
Vol 568-570 ◽  
pp. 320-325 ◽  
Author(s):  
Feng Shan Huang ◽  
Li Chen
Keyword(s):  
Coordinate System ◽  
Camera Calibration ◽  
Characteristic Point ◽  
Coordinate Measuring Machine ◽  
Ccd Camera ◽  
Mathematic Model ◽  
Calibration Method ◽  
Calibration Characteristic ◽  
Standard Sphere ◽  
Measuring Machine

A new CCD camera calibration method based on the translation of Coordinate Measuring Machine (CMM) is proposed. The CMM brings the CCD camera to produce the relative translation with respect to the center of the white ceramic standard sphere along the X, Y, Z axis, and the coordinates of the different positions of the calibration characteristic point in the probe coordinate system can be generated. Meanwhile, the camera captures the image of the white ceramic standard sphere at every position, and the coordinates of the calibration characteristic point in the computer frame coordinate system can be registered. The calibration mathematic model was established, and the calibration steps were given and the calibration system was set up. The comparing calibration result shows that precision of this method is equivalent to that of the special calibration method, and the difference between the calibrating data of these two methods is within ±1μm.

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.

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