Vertical Position Identification of the Machine Vision System in the Mineshaft for the Purposes of Diagnostic Image Processing of the Mineshaft Lining Surface

2015 ◽  
pp. 157-165
Author(s):  
Henryk Kleta ◽  
Adam Heyduk ◽  
Jarosław Joostberens
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Vision System ◽  
Vertical Position ◽  
Machine Vision System ◽  
Diagnostic Image ◽  
Diagnostic Image Processing

Research of Machine Vision System about Robot Soccer Based on the HSV

2010 ◽  
Vol 121-122 ◽  
pp. 807-812
Author(s):  
Sheng Rong Lu ◽  
Huan Long Guo
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Process Design ◽  
Vision System ◽  
Processing Technology ◽  
Machine Vision System ◽  
Identification Process ◽  
Image Access ◽  
Processing Factors ◽  
Rgb Image

In this paper, including the introduction of image processing and image processing factors influence the discussion, after the RGB image access to the transformation of HSV, mainly through the robot to select the image of the identification process design, completed the capture of a robot A specific color of the entity, after the robot moves to give you accurate basis for the judgment. First of all, the introduction for images on the basis of the relevant knowledge is presented. Second, the image and the image of the divisions are briefly introduced. Third, we proposed the image factors and image processing technology. Fourth, conversion from RGB to HSV model is presented. Finally, we designed the image of the robot to access and identify procedures modular.

scholarly journals Measurements of Tool Wear Parameters Using Machine Vision System

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Avinash A. Thakre ◽  
Aniruddha V. Lad ◽  
Kiran Mala
Keyword(s):  
Image Processing ◽  
Tool Wear ◽  
Machine Vision ◽  
Vision System ◽  
Average Error ◽  
Scanning Electron Micrographs ◽  
Machine Vision System ◽  
Machining Time ◽  
Wear Area ◽  
Carbide Inserts

Monitoring tool wear is very important in machining industry as it may result in loss of dimensional accuracy and quality of finished product. This work includes the development of machine vision system for the direct measurement of flank wear of carbide cutting tool inserts. This system consists of a digital camera to capture the tool wear image, a good light source to illuminate the tool, and a computer for image processing. A new approach of inline automatic calibration of a pixel is proposed in this work. The captured images of carbide inserts are processed, and the segmented tool wear zone has been obtained by image processing. The vision system extracts tool wear parameters such as average tool wear width, tool wear area, and tool wear perimeter. The results of the average tool wear width obtained from the vision system are experimentally validated with those obtained from the digital microscope. An average error of 3% was found for measurements of all 12 carbide inserts. Scanning electron micrographs of the wear zone indicate the severe abrasion marks and damage to the cutting edge for higher machining time. This study indicates that the efficient and reliable vision system can be developed to measure the tool wear parameters.

scholarly journals Real-Time Detection of Strawberry Powdery Mildew Disease Using a Mobile Machine Vision System

Agronomy ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 1027
Author(s):  
Md Sultan Mahmud ◽  
Qamar U. Zaman ◽  
Travis J. Esau ◽  
Young K. Chang ◽  
G. W. Price ◽  
...  
Keyword(s):  
Image Processing ◽  
Powdery Mildew ◽  
Machine Vision ◽  
Detection System ◽  
Vision System ◽  
Machine Vision System ◽  
Field Site ◽  
System A ◽  
Processing Program ◽  
Powdery Mildew Disease

Strawberry cropping system relies heavily on proper disease management to maintain high crop yield. Powdery mildew, caused by Sphaerotheca macularis (Wall. Ex Fries) is one of the major leaf diseases in strawberry which can cause significant yield losses up to 70%. Field scouts manually walk beside strawberry fields and visually observe the plants to monitor for powdery mildew disease infection each week during summer months which is a laborious and time-consuming endeavor. The objective of this research was to increase the efficiency of field scouting by automatically detecting powdery mildew disease in strawberry fields by using a real-time machine vision system. A global positioning system, two cameras, a custom image processing program, and a ruggedized laptop computer were utilized for development of the disease detection system. The custom image processing program was developed using color co-occurrence matrix-based texture analysis along with artificial neural network technique to process and classify continuously acquired image data simultaneously. Three commercial strawberry field sites in central Nova Scotia were used to evaluate the performance of the developed system. A total of 36 strawberry rows (~1.06 ha) were tested within three fields and powdery mildew detected points were measured manually followed by automatic detection system. The manually detected points were compared with automatically detected points to ensure the accuracy of the developed system. Results of regression and scatter plots revealed that the system was able to detect disease having mean absolute error values of 4.00, 3.42, and 2.83 per row and root mean square error values of 4.12, 3.71, and 3.00 per row in field site-I, field site-II, and field site-III, respectively. The slight deviation in performance was likely caused by high wind speeds (>8 km h−1), leaf overlapping, leaf angle, and presence of spider mite disease during field testing.

scholarly journals Bilgisayarlı Görüntüleme Sistemi: Gıda Endüstrisinde Kullanımı ve Uygulamaları

2019 ◽  
Vol 7 (7) ◽  
pp. 989
Author(s):  
Pinar Balkir ◽  
Kemal Kemahlıoğlu ◽  
Ufuk Yücel
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Fruits And Vegetables ◽  
Vision System ◽  
Computer Hardware ◽  
Machine Vision System ◽  
Food Sector ◽  
Image Capture ◽  
Wide Range ◽  
Marine Products

Machine vision system is a combination of camera, image capture card, computer hardware and image processing technology. Safe foods are highly preferred by consumers today and accordingly, machine vision system has the edge on food sector for ensuring qualitative data and accelerating some certain processes. Machine vision system, which is more accurate, reliable and faster than conventional methods, has been used in wide range of applications in the inspection of cereals, fruits and vegetables, meats and marine products and some other processed foods in combination with convenient image processing and analysing algorithms. Considering the objectivity, promptness, economy and effectiveness as the chief advantages, the system makes progress as an alternative method in the sector.

Multifunctional stereoscopic machine vision system with multiple 3D outputs

2020 ◽  
Keyword(s):  
Machine Vision ◽  
International Symposium ◽  
Fast Track ◽  
Vision System ◽  
Machine Vision System ◽  
Stereoscopic Displays ◽  
Electronic Imaging

Fast track article for IS&T International Symposium on Electronic Imaging 2020: Stereoscopic Displays and Applications proceedings.

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