Computer vision system: a tool for evaluating the quality of wheat in a grain tank

2018 ◽  
Author(s):  
Ivan Konovalenko ◽  
Aleksandr Shkanaev ◽  
Uryi Minkin ◽  
Aleksei Panchenko ◽  
Dmitry Putintsev ◽  
...  
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Computer Vision System ◽  
System A

Vision-Based Precision Deburring and Edge Breaking Process Quality Control

2020 ◽  
Author(s):  
Kartik Gupta ◽  
Cindy Grimm ◽  
Burak Sencer ◽  
Ravi Balasubramanian
Keyword(s):  
Computer Vision ◽  
Quality Control ◽  
Vision System ◽  
Quality Measures ◽  
Cad Model ◽  
Computer Vision System ◽  
Part Geometry ◽  
Specialized Hardware ◽  
Original Part

Abstract This paper presents a computer vision system for evaluating the quality of deburring and edge breaking on aluminum and steel blocks. This technique produces both quantitative (size) and qualitative (quality) measures of chamfering operation from images taken with an off-the-shelf camera. We demonstrate that the proposed computer vision system can detect edge chamfering geometry within a 1–2mm range. The proposed technique does not require precise calibration of the camera to the part nor specialized hardware beyond a macro lens. Off-the-shelf components and a CAD model of the original part geometry are used for calibration. We also demonstrate the effectiveness of the proposed technique on edge breaking quality control.

scholarly journals OUTLINING A RELEVANT UNDERGRADUATE COURSE ON COMPUTER VISION

2012 ◽  
Author(s):  
Gabriel Thomas
Keyword(s):  
Computer Vision ◽  
Mobile Devices ◽  
Vision System ◽  
Computer Vision System ◽  
System A ◽  
Software And Hardware

Having offered a computer vision course as a 4th year undergraduate elective for almost a decade now prompt me to re-evaluate it, not just with the idea of adding new trends seen at international symposia on a yearly basis but evaluating the course taking into consideration what can be seen as needed outside academia and within academia as a preparation for industry jobs and further studies and research. Thus, this paper suggests the different topics that such a course must cover in order to have a strong background on the necessary steps needed to successfully implement a computer vision system. A discussion regarding software and hardware tools involves what I perceive to be an importance towards covering computer vision based on mobile devices.

scholarly journals Computer Vision System: A Better Tool for Assessing Pork and Beef Colour than a Standard Colourimeter

2020 ◽  
Vol 61 (2) ◽  
pp. 153-160
Author(s):  
Bojana Milovanović ◽  
Ilija Đekić ◽  
Bartosz Sołowiej ◽  
Saša Novaković ◽  
Vesna Đorđevic ◽  
...  
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Computer Vision System ◽  
System A

scholarly journals Objective Evaluation of External Quality of Broccoli Heads Using a Computer Vision System

2016 ◽  
Vol 17 (4) ◽  
pp. 107-113 ◽  
Author(s):  
Yoshio MAKINO ◽  
Aoi WAKATSUKI ◽  
Genki AMINO ◽  
Seiichi OSHITA ◽  
Akari SATO ◽  
...  
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Objective Evaluation ◽  
Computer Vision System ◽  
External Quality

Research on Detection of Micro Plastic Gear Tooth Based on Dummy Circle Scan Method

2010 ◽  
Vol 37-38 ◽  
pp. 1002-1005
Author(s):  
Zhen Xiang Zhang ◽  
Kun Wang ◽  
Xun Yang ◽  
Lian Qing Chen
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Gear Tooth ◽  
Location Theory ◽  
Automatic Inspection ◽  
Computer Vision System ◽  
Image Preprocessing ◽  
Pixel Location ◽  
Plastic Gears

The quality of micro plastic gears was inspected with the image recognition technology herein. Focusing on the situation that gears’ defects were uncertain, the construction of computer vision system and the theories, technologies of digital image acquisition, image preprocessing, image segmentation as well as the sub-pixel location theory were studied thoroughly. A dummy circle scan method is presented to realize the gear tooth inspection, and the results indicate that it can meet request on the automatic inspection of micro plastic gears.

scholarly journals Measurement of Gem Colour Using a Computer Vision System: A Case Study with Jadeite-Jade

Minerals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 791
Author(s):  
Sufei Zhang ◽  
Ying Guo
Keyword(s):  
Computer Vision ◽  
Regression Model ◽  
Vision System ◽  
Expert Group ◽  
Group Test ◽  
System A ◽  
Real Objects ◽  
Practical Tool ◽  
Almost All

This paper introduces computer vision systems (CVSs), which provides a new method to measure gem colour, and compares CVS and colourimeter (CM) measurements of jadeite-jade colour in the CIELAB space. The feasibility of using CVS for jadeite-jade colour measurement was verified by an expert group test and a reasonable regression model in an experiment involving 111 samples covering almost all jadeite-jade colours. In the expert group test, more than 93.33% of CVS images are considered to have high similarities with real objects. Comparing L*, a*, b*, C*, h, and ∆E* (greater than 10) from CVS and CM tests indicate that significant visual differences exist between the measured colours. For a*, b*, and h, the R2 of the regression model for CVS and CM was 90.2% or more. CVS readings can be used to predict the colour value measured by CM, which means that CVS technology can become a practical tool to detect the colour of jadeite-jade.

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