scholarly journals The Machine Vision Measurement Module of the Modularized Flexible Precision Assembly Station for Assembly of Micro- and Meso-Sized Parts

Micromachines ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 918
Author(s):  
Zhiyong Zhang ◽  
Xiaodong Wang ◽  
Hongtu Zhao ◽  
Tongqun Ren ◽  
Zheng Xu ◽  
...  
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Principal Point ◽  
Online Calibration ◽  
Vision Measurement ◽  
Final Integration ◽  
On Line ◽  
Orientation Deviation ◽  
Set Up ◽  
Different Diameters

The machine vision measurement module is indispensable for the Modularized Flexible Precision Assembly Station (MFPAS), which is a fully automatic assembly system being developed at Dalian University of Technology (DUT). MFPAS consists of basic and additional modules, and are expected to be flexible, expandable, and re-configurable to adapt to a variety of parts with a large size range, requiring the machine vision measurement module to be able to achieve accurate measurement of position, as well as orientation of the parts with different size scale. An automatic zooming vision system was set up for evaluation and final integration in MFPAS. Pixel equivalent, principal point and orientation deviation of images were analyzed and experimentally studied using different magnifications of the lens. A new template with circular patterns of different diameters was designed for zoom-lens calibration. The experiments show that the measurement error caused by the variation of the pixel equivalent, principal point and orientation is estimated under 10 μm without online calibration. When high accuracy is required, online calibration can be employed during assembly. The evaluation results of the vision system with or without on-line calibration were given for a better trade-off between accuracy and efficiency during assembly.

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.

A machine vision system for on-line removal of contaminants in wool

Mechatronics ◽  
2006 ◽  
Vol 16 (5) ◽  
pp. 243-247 ◽  
Author(s):  
Zhenwei Su ◽  
Gui Yun Tian ◽  
Chunhua Gao
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Machine Vision System ◽  
On Line ◽  
Removal Of Contaminants

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 Detection of Foreign Materials in Wheat Kernels using Boundary Descriptors

2020 ◽  
Vol 9 (6) ◽  
pp. 1001-1009
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Recognition Task ◽  
Machine Vision System ◽  
On Line ◽  
Neural Classifier ◽  
Foreign Materials ◽  
Impurity Elements ◽  
Wheat Kernels ◽  
Regional Boundary

The present paper reports the development of a machine vision system for quality inspection of wheat using kernel shape attribute. Shape attribute of agricultural products including wheat kernels is extremely difficult to quantify in digital computation. A new method is proposed in the present work to quantify shape attribute of wheat kernels using regional boundary descriptors. Recognition task in the proposed machine vision system is carried out by neural classifier trained with Levenberg-Marquardt (LM) based supervised learning. Proposed neural classifier was executed using feed-forward backpropagation based three layer artificial neural network. Experimental results indicate more than 98.1% overall average classification accuracy for the involved wheat and impurity elements in the present work. The results of present study are quite promising and the proposed machine vision system has potential future for on-line inspection of agriculture produce in real time environment.

scholarly journals THE DESIGN OF GROUND AIR DUAL PURPOSE AGRICULTURAL INFORMATION ACQUISITION ROBOT

2020 ◽  
pp. 259-268
Author(s):  
Qinlan Li
Keyword(s):  
Machine Vision ◽  
Information Acquisition ◽  
Vision System ◽  
Control Group ◽  
Machine Vision System ◽  
Image Processing Algorithm ◽  
Dual Purpose ◽  
Growth State ◽  
Good Ability ◽  
Set Up

The key to the design of the ground air dual-purpose agricultural information acquisition robot is the application of machine vision technology to realize the collection of crop growth state information. This research mainly designs the machine vision system of the ground air dual-purpose agricultural information acquisition robot, including hardware, software and image processing algorithm. The machine vision system designed in this paper can effectively complete the collection of crop status information. In order to verify the effectiveness of machine vision system, blueberry was used as the experimental object. The control group was set up indoor and outdoor, the fruit condition and quality information were detected, and the blueberry yield was estimated according to the test results. The experimental results show that the image segmentation algorithm in the vision system can identify blueberry fruit well, and the system has strong information analysis ability, and can accurately predict the quality and yield of blueberry fruit according to the image. It can be seen that the machine vision system has a good ability of information acquisition and recognition, which has a high reference significance for the design and research of the ground air dual-purpose agricultural information acquisition robot.

scholarly journals Machine vision system for on-line wholesomeness inspection of poultry carcasses

2010 ◽  
Vol 89 (6) ◽  
pp. 1252-1264 ◽  
Author(s):  
C.-C. Yang ◽  
K. Chao ◽  
M.S. Kim ◽  
D.E. Chan ◽  
H.L. Early ◽  
...  
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Machine Vision System ◽  
On Line

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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