Assessment of computer vision methods for motion tracking of planar mechanisms

2021 ◽  
pp. 095440622110498
Author(s):  
Juan C Arellano-González ◽  
Hugo I Medellín-Castillo ◽  
J. Jesús Cervantes-Sánchez ◽  
Mario A García-Murillo
Keyword(s):  
Computer Vision ◽  
Motion Tracking ◽  
Low Cost ◽  
Homogeneous Solution ◽  
Planar Mechanisms ◽  
Motion Trajectories ◽  
Operation Conditions ◽  
Computational Performance ◽  
Calibration Matrix

One of the main challenges on the use of planar mechanisms is to verify and monitor that the trajectories described by the mechanism correspond to those originally required. However, very few research studies have focused on tracking and monitoring the motion of target points located on the mechanisms during operation conditions. In this paper, a comparative study to evaluate the performance of several computer vision methods (CVMs) when used in motion tracking of planar mechanisms is presented. The aim is to compare and identify the best CVM, in terms of precision, speed, low cost, and computational performance, to track the movement of planar mechanisms. For this purpose, a case study corresponding to a planar four-bar mechanism is selected and analysed. The results show that the vision methods based on the homogeneous and non-homogeneous solution of the camera calibration matrix are a technological alternative for monitoring motion trajectories of planar mechanisms.

Low Temperature Fault Isolation Using Soft Defect Localization

2012 ◽  
Author(s):  
Kristopher D. Staller
Keyword(s):  
Low Temperatures ◽  
Laser Scanning ◽  
Low Cost ◽  
Fault Isolation ◽  
Laser Scanning Microscopy ◽  
Cold Temperature ◽  
Multiple Point ◽  
Defect Localization ◽  
Low Levels

Abstract Cold temperature failures are often difficult to resolve, especially those at extreme low levels (< -40°C). Momentary application of chill spray can confirm the failure mode, but is impractical during photoemission microscopy (PEM), laser scanning microscopy (LSM), and multiple point microprobing. This paper will examine relatively low-cost cold temperature systems that can hold samples at steady state extreme low temperatures and describe a case study where a cold temperature stage was combined with LSM soft defect localization (SDL) to rapidly identify the cause of a complex cold temperature failure mechanism.

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.

scholarly journals A Regenerative Business Model with Flexible, Modular and Scalable Processes in A Post-Covid Era: The Case of The Spinning Mesh Disc Reactor (SMDR)

2021 ◽  
Vol 13 (12) ◽  
pp. 6944
Author(s):  
Emma Anna Carolina Emanuelsson ◽  
Aurelie Charles ◽  
Parimala Shivaprasad
Keyword(s):  
Business Model ◽  
Low Cost ◽  
Sustainable Manufacturing ◽  
Sustainable Business ◽  
Capital Costs ◽  
Implementing Change ◽  
Chemical Manufacturing ◽  
Manufacturing Techniques ◽  
Flexible Operation

With stringent environmental regulations and a new drive for sustainable manufacturing, there is an unprecedented opportunity to incorporate novel manufacturing techniques. Recent political and pandemic events have shown the vulnerability to supply chains, highlighting the need for localised manufacturing capabilities to better respond flexibly to national demand. In this paper, we have used the spinning mesh disc reactor (SMDR) as a case study to demonstrate the path forward for manufacturing in the post-Covid world. The SMDR uses centrifugal force to allow the spread of thin film across the spinning disc which has a cloth with immobilised catalyst. The modularity of the design combined with the flexibility to perform a range of chemical reactions in a single equipment is an opportunity towards sustainable manufacturing. A global approach to market research allowed us to identify sectors within the chemical industry interested in novel reactor designs. The drivers for implementing change were identified as low capital cost, flexible operation and consistent product quality. Barriers include cost of change (regulatory and capital costs), limited technical awareness, safety concerns and lack of motivation towards change. Finally, applying the key features of a Sustainable Business Model (SBM) to SMDR, we show the strengths and opportunities for SMDR to align with an SBM allowing for a low-cost, sustainable and regenerative system of chemical manufacturing.

scholarly journals An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 343
Author(s):  
Kim Bjerge ◽  
Jakob Bonde Nielsen ◽  
Martin Videbæk Sepstrup ◽  
Flemming Helsing-Nielsen ◽  
Toke Thomas Høye
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Vision System ◽  
Low Cost ◽  
Light Trap ◽  
Automatic Monitoring ◽  
Light Sources ◽  
Monitoring Methods ◽  
Computer Vision System ◽  
Substantial Investment

Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.

scholarly journals A computer vision-based object detection and counting for COVID-19 protocol compliance: a case study of Jakarta

2020 ◽  
Author(s):  
Muhammad Lanang Afkaar Ar ◽  
Sulthan Muzakki Adytia S ◽  
Yudhistira Nugraha ◽  
Farizah Rizka R ◽  
Andy Ernesto ◽  
...  
Keyword(s):  
Computer Vision ◽  
Object Detection ◽  
Detection And Counting ◽  
Protocol Compliance

scholarly journals Comparative Analysis of Low-Cost GNSS OEM Board K706 AND BX316 (Case Study: Bulusidokare Village Sidoarjo Regency)

2021 ◽  
Vol 731 (1) ◽  
pp. 012024
Author(s):  
M N Cahyadi ◽  
E Y Handoko ◽  
R Mardiyanto ◽  
I M Anjasmara ◽  
Khomsin ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Low Cost

MECHANIZATION OF POTATO GRADING ON SMALL-SCALE FARMS: A CASE STUDY FROM PERU

2005 ◽  
Vol 41 (1) ◽  
pp. 81-92 ◽  
Author(s):  
G. P. BUTLER ◽  
T. BERNET ◽  
K. MANRIQUE
Keyword(s):  
Developing Countries ◽  
Market Integration ◽  
Low Cost ◽  
Farming System ◽  
Agricultural Products ◽  
Small Scale ◽  
Critical Aspect ◽  
Small Scale Farmers ◽  
Important Cash Crop

Potatoes are an important cash crop for small-scale producers worldwide. The move away from subsistence to commercialized farming, combined with the rapid growth in demand for processed agricultural products in developing countries, implies that small-scale farmers and researchers alike must begin to respond to these market changes and consider post-harvest treatment as a critical aspect of the potato farming system. This paper presents and assesses a low cost potato-grading machine that was designed explicitly to enable small-scale potato growers to sort tubers by size for supply to commercial processors. The results of ten experiments reveal that the machine achieves an accuracy of sort similar to commercially available graders. The machine, which uses parallel conical rollers, has the capacity to grade different tuber shapes and to adjust sorting classes, making it suitable for locations with high potato diversity. Its relatively low cost suggests that an improved and adapted version of this machine might enhance market integration of small-scale potato producers not only in Peru, but in other developing countries as well.

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