scholarly journals A Novel Concentric Circular Coded Target, and Its Positioning and Identifying Method for Vision Measurement under Challenging Conditions

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 855
Author(s):  
Yan Liu ◽  
Xin Su ◽  
Xiang Guo ◽  
Tao Suo ◽  
Qifeng Yu
Keyword(s):  
Vision System ◽  
Viewing Angle ◽  
Robust Identification ◽  
Detection Algorithms ◽  
Vision Measurement ◽  
Robust Recognition ◽  
Eccentricity Error ◽  
Local Image ◽  
Wing Deformation ◽  
Background Area

Coded targets have been demarcated as control points in various vision measurement tasks such as camera calibration, 3D reconstruction, pose estimation, etc. By employing coded targets, matching corresponding image points in multi images can be automatically realized which greatly improves the efficiency and accuracy of the measurement. Although the coded targets are well applied, particularly in the industrial vision system, the design of coded targets and its detection algorithms have encountered difficulties, especially under the conditions of poor illumination and flat viewing angle. This paper presents a novel concentric circular coded target (CCCT), and its positioning and identifying algorithms. The eccentricity error has been corrected based on a practical error-compensation model. Adaptive brightness adjustment has been employed to address the problems of poor illumination such as overexposure and underexposure. The robust recognition is realized by perspective correction based on four vertices of the background area in the CCCT local image. The simulation results indicate that the eccentricity errors of the larger and smaller circles at a large viewing angle of 70° are reduced by 95% and 77% after correction by the proposed method. The result of the wing deformation experiment demonstrates that the error of the vision method based on the corrected center is reduced by up to 18.54% compared with the vision method based on only the ellipse center when the wing is loaded with a weight of 6 kg. The proposed design is highly applicable, and its detection algorithms can achieve accurate positioning and robust identification even in challenging environments.

2-D Circle Measurement System for Small Rule Parts Based on Machine Vision

2011 ◽  
Vol 291-294 ◽  
pp. 2624-2629 ◽  
Author(s):  
Qing Hua Wu ◽  
Na Dai ◽  
Tao He
Keyword(s):  
Machine Vision ◽  
Measurement System ◽  
Vision System ◽  
Measured Data ◽  
Machine Vision System ◽  
Mechanical Parts ◽  
Vision Measurement ◽  
Ring Radius ◽  
On Line ◽  
Calibration Mark

A Circle-shape is an important figure in most small rule mechanical parts, and usually be measured to get the radius or used as a stand calibration mark. In this paper, a 2-D circle measurement system for small rule mechanical parts based on machine vision is designed and built. The basic components and work principle of the machine vision measurement system are introduced, and the measurement produce is designed and discussed. An available algorithm for circle contour detected and fitted is described. Using this algorithm, the measurement software flow and architecture are built and the software system realized in the Microsoft visual studio program platform. Certainly, the calibration of machine vision system is introduced also. Using the system and method introduced above, an experiment is designed to measure the outer ring radius of one certain model bearing. The measured data is processed and analyzed. Through the experiment and result, it can be found that the measurement system can get relatively high precision and the measurement method is relatively steady, and the system precision and speed can be suit for the demand of on-line and real-time circle measurement.

scholarly journals Precise calibration of binocular vision system used for vision measurement

2014 ◽  
Vol 22 (8) ◽  
pp. 9134 ◽  
Author(s):  
Yi Cui ◽  
Fuqiang Zhou ◽  
Yexin Wang ◽  
Liu Liu ◽  
He Gao
Keyword(s):  
Binocular Vision ◽  
Vision System ◽  
Vision Measurement ◽  
Binocular Vision System

The Calibration of Binocular Stereo Vision for the Camera Based on Machine Vision Measurement

2014 ◽  
Vol 701-702 ◽  
pp. 361-366
Author(s):  
Xiao Jing Yang ◽  
Si Qi Wang
Keyword(s):  
Machine Vision ◽  
Camera Calibration ◽  
Stereo Vision ◽  
Vision System ◽  
Calibration Target ◽  
Vision Measurement ◽  
Matlab Program ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Left And Right

Camera calibration is the most important stage of machine vision measurement. The principle and method of camera calibration for binocular stereo vision system are introduced and the left and right CCD are respectively calibrated by using the prepared calibration target and the MATLAB program. Then internal and external camera parameters are obtained by the calibration experiments. The experimental results show that the calibration results have high precision.

scholarly journals THERMAL TEXTURE SELECTION AND CORRECTION FOR BUILDING FACADE INSPECTION BASED ON THERMAL RADIANT CHARACTERISTICS

2018 ◽  
Vol XLII-2 ◽  
pp. 585-591 ◽  
Author(s):  
D. Lin ◽  
M. Jarzabek-Rychard ◽  
D. Schneider ◽  
H.-G. Maas
Keyword(s):  
3D Model ◽  
Incident Angle ◽  
Texture Mapping ◽  
Image Sequence ◽  
Calibration Method ◽  
Viewing Angle ◽  
Thermal Camera ◽  
Building Facade ◽  
Local Image ◽  
Rgb Image

An automatic building façade thermal texture mapping approach, using uncooled thermal camera data, is proposed in this paper. First, a shutter-less radiometric thermal camera calibration method is implemented to remove the large offset deviations caused by changing ambient environment. Then, a 3D façade model is generated from a RGB image sequence using structure-from-motion (SfM) techniques. Subsequently, for each triangle in the 3D model, the optimal texture is selected by taking into consideration local image scale, object incident angle, image viewing angle as well as occlusions. Afterwards, the selected textures can be further corrected using thermal radiant characteristics. Finally, the Gauss filter outperforms the voted texture strategy at the seams smoothing and thus for instance helping to reduce the false alarm rate in façade thermal leakages detection. Our approach is evaluated on a building row façade located at Dresden, Germany.

scholarly journals A new vision measurement method based on active object gazing

2017 ◽  
Vol 14 (4) ◽  
pp. 172988141771598 ◽  
Author(s):  
De Xu ◽  
Qingbin Wang
Keyword(s):  
Measurement Method ◽  
Measurement Accuracy ◽  
Rotation Angle ◽  
Vision System ◽  
Three Dimensional ◽  
Active Object ◽  
Intrinsic Parameters ◽  
Vision Measurement ◽  
Cartesian Space ◽  
New Vision

A new vision measurement system is developed with two cameras. One is fixed in pose to serve as a monitor camera. It finds and tracks objects in image space. The other is actively rotated to track the object in Cartesian space, working as an active object-gazing camera. The intrinsic parameters of the monitor camera are calibrated. The view angle corresponding to the object is calculated from the object’s image coordinates and the camera’s intrinsic parameters. The rotation angle of the object-gazing camera is measured with an encoder. The object’s depth is computed with the rotation angle and the view angle. Then the object’s three-dimensional position is obtained with its depth and normalized imaging coordinates. The error analysis is provided to assess the measurement accuracy. The experimental results verify the effectiveness of the proposed vision system and measurement method.

A target tracking and location robot system based on omnistereo vision

2017 ◽  
Vol 44 (6) ◽  
pp. 741-753 ◽  
Author(s):  
Chengtao Cai ◽  
Bing Fan ◽  
Xiangyu Weng ◽  
Qidan Zhu ◽  
Li Su
Keyword(s):  
Image Processing ◽  
Target Tracking ◽  
Vision System ◽  
Computation Time ◽  
Processing Method ◽  
Omnidirectional Vision ◽  
Robot System ◽  
Content Type ◽  
Tracking Method ◽  
Local Image

Purpose Because of their large field of view, omnistereo vision systems have been widely used as primary vision sensors in autonomous mobile robot tasks. The purpose of this article is to achieve real-time and accurate tracking by the omnidirectional vision robot system. Design/methodology/approach The authors provide in this study the key techniques required to obtain an accurate omnistereo target tracking and location robot system, including stereo rectification and target tracking in complex environment. A simple rectification model is proposed, and a local image processing method is used to reduce the computation time in the localization process. A target tracking method is improved to make it suitable for omnidirectional vision system. Using the proposed methods and some existing methods, an omnistereo target tracking and location system is established. Findings The experiments are conducted with all the necessary stages involved in obtaining a high-performance omnistereo vision system. The proposed correction algorithm can process the image in real time. The experimental results of the improved tracking algorithm are better than the original algorithm. The statistical analysis of the experimental results demonstrates the effectiveness of the system. Originality/value A simple rectification model is proposed, and a local image processing method is used to reduce the computation time in the localization process. A target tracking method is improved to make it suitable for omnidirectional vision system. Using the proposed methods and some existing methods, an omnistereo target tracking and location system is established.

scholarly journals Vision-Based Three-Dimensional Reconstruction and Monitoring of Large-Scale Steel Tubular Structures

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Yunchao Tang ◽  
Mingyou Chen ◽  
Yunfan Lin ◽  
Xueyu Huang ◽  
Kuangyu Huang ◽  
...  
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Learning Algorithm ◽  
Vision System ◽  
Three Dimensional ◽  
Steel Tube ◽  
Dynamic Monitoring ◽  
Complex Environments ◽  
Cross Sectional ◽  
Vision Measurement

A four-ocular vision system is proposed for the three-dimensional (3D) reconstruction of large-scale concrete-filled steel tube (CFST) under complex testing conditions. These measurements are vitally important for evaluating the seismic performance and 3D deformation of large-scale specimens. A four-ocular vision system is constructed to sample the large-scale CFST; then point cloud acquisition, point cloud filtering, and point cloud stitching algorithms are applied to obtain a 3D point cloud of the specimen surface. A point cloud correction algorithm based on geometric features and a deep learning algorithm are utilized, respectively, to correct the coordinates of the stitched point cloud. This enhances the vision measurement accuracy in complex environments and therefore yields a higher-accuracy 3D model for the purposes of real-time complex surface monitoring. The performance indicators of the two algorithms are evaluated on actual tasks. The cross-sectional diameters at specific heights in the reconstructed models are calculated and compared against laser rangefinder data to test the performance of the proposed algorithms. A visual tracking test on a CFST under cyclic loading shows that the reconstructed output well reflects the complex 3D surface after correction and meets the requirements for dynamic monitoring. The proposed methodology is applicable to complex environments featuring dynamic movement, mechanical vibration, and continuously changing features.

Effect of Calibration Grid Size and Position on Machine Vision Measurement

2012 ◽  
Vol 220-223 ◽  
pp. 1303-1306
Author(s):  
Jie Sun ◽  
Zeng Pu Xu ◽  
Cong Ling Zhou ◽  
Yong Qiang Wang
Keyword(s):  
Machine Vision ◽  
Measurement Errors ◽  
Measurement Accuracy ◽  
Corner Point ◽  
Vision System ◽  
Grid Size ◽  
Machine Vision System ◽  
Opposite Edge ◽  
Measuring Point ◽  
Vision Measurement

In order to improve the measurement accuracy of machine vision, this paper focuses on the effect of calibration grid size and position on machine vision measurement accuracy by analysing the measurement error of the points inside and outside of the grid. The experimental results show that the measurement accuracy of the internal points is higher than that of the external points. The measurement errors increase firstly, then decrease, increase, and finally decrease which measuring point from the edge to the opposite edge in the calibration grid. While measurement errors of outside points increases with the increasing distance to the corner point. If the center of calibration grid coincides with the center of calibration board, measurement accuracy is high. However, if the center of calibration grid doesn't coincide with the center of calibration board, measurement accuracy is low. This results may provide direct means for the application of machine vision system in engineering.

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