Improved robust and accurate camera calibration method used for machine vision application

2008 ◽  
Vol 47 (11) ◽  
pp. 117201 ◽  
Author(s):  
Zhiyong Zhang
Keyword(s):  
Machine Vision ◽  
Camera Calibration ◽  
Calibration Method ◽  
Machine Vision Application ◽  
Vision Application

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.

A Modelling of Stereo Matching Algorithm for Machine Vision Application

2019 ◽  
pp. 499-508
Author(s):  
Rostam Affendi Hamzah ◽  
A. F. Kadmin ◽  
S. F. Abd Gani ◽  
N. Mohamood ◽  
A N. A. Jahari ◽  
...  
Keyword(s):  
Machine Vision ◽  
Stereo Matching ◽  
Matching Algorithm ◽  
Machine Vision Application ◽  
Vision Application

Machine Vision Application on Science and Industry

2019 ◽  
pp. 233-254
Author(s):  
Bassem S. M. Zohdy ◽  
Mahmood A. Mahmood ◽  
Nagy Ramadan Darwish ◽  
Hesham A. Hefny
Keyword(s):  
Machine Vision ◽  
Medical Research ◽  
Real Time ◽  
Medical Images ◽  
Deep Understanding ◽  
Great Opportunity ◽  
Material Systems ◽  
Machine Vision Application ◽  
Real Time Detection ◽  
Vision Application

Machine vision studies opens a great opportunity for different domains as manufacturing, agriculture, aquaculture, medical research, also research studies and applications for better understanding of processes and operations. As scientists' efforts had been directed towards deep understanding of the particular material systems or particular classes of types of specific fruits, or diagnosis of patients through medical images classification and analysis, also real time detection and inspection of malfunction piece, or process, as various domains witnessed advancement through using machine vision techniques and methods.

Influence of Sample Defocus and Large Thickness on Measurement Error in Machine Vision Application

2015 ◽  
Vol 35 (8) ◽  
pp. 0815002
Author(s):  
来先家 Lai Xianjia ◽  
徐文东 Xu Wendong ◽  
赵成强 Zhao Chengqiang ◽  
肖阳 Xiao Yang
Keyword(s):  
Measurement Error ◽  
Machine Vision ◽  
Large Thickness ◽  
Machine Vision Application ◽  
Vision Application

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.

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