Real-Time Quality Control of Heat Sealed Bottles Using Thermal Images and Artificial Neural Network
Quality control of heat sealed bottles is very important to minimize waste and in some cases protect people’s health. The present paper describes a case study where an automated non invasive and non destructive quality control system was designed to assess the quality of the seals of bottles contain...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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MDPI AG
2021-02-01
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Series: | Journal of Imaging |
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Online Access: | https://www.mdpi.com/2313-433X/7/2/24 |
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author | Samuel Cruz António Paulino Joao Duraes Mateus Mendes |
author_facet | Samuel Cruz António Paulino Joao Duraes Mateus Mendes |
author_sort | Samuel Cruz |
collection | DOAJ |
description | Quality control of heat sealed bottles is very important to minimize waste and in some cases protect people’s health. The present paper describes a case study where an automated non invasive and non destructive quality control system was designed to assess the quality of the seals of bottles containing pesticide. In this case study, the integrity of the seals is evaluated using an artificial neural network based on images of the seals processed with computer vision techniques. Because the seals are not directly visible from the bottle exterior, the images are infrared pictures obtained using a thermal camera. The method is non invasive, automated, and can be applied to common conveyor belts currently used in industrial plants. The results show that the inspection process is effective in identifying defective seals with a precision of 98.6% and a recall of 100% and because it is automated it can be scaled up to large bottle processing plants. |
first_indexed | 2024-03-09T05:56:51Z |
format | Article |
id | doaj.art-fedf305eba0240cd8736ed8b63717fca |
institution | Directory Open Access Journal |
issn | 2313-433X |
language | English |
last_indexed | 2024-03-09T05:56:51Z |
publishDate | 2021-02-01 |
publisher | MDPI AG |
record_format | Article |
series | Journal of Imaging |
spelling | doaj.art-fedf305eba0240cd8736ed8b63717fca2023-12-03T12:13:28ZengMDPI AGJournal of Imaging2313-433X2021-02-01722410.3390/jimaging7020024Real-Time Quality Control of Heat Sealed Bottles Using Thermal Images and Artificial Neural NetworkSamuel Cruz0António Paulino1Joao Duraes2Mateus Mendes3Polytechnic of Coimbra, Coimbra Engineering Academy, R. Pedro Nunes, 3030-199 Coimbra, PortugalPolytechnic of Coimbra, Higher School of Technology and Management, R. General Santos Costa, 3400-124 Oliveira do Hospital, PortugalPolytechnic of Coimbra, Coimbra Engineering Academy, R. Pedro Nunes, 3030-199 Coimbra, PortugalPolytechnic of Coimbra, Coimbra Engineering Academy, R. Pedro Nunes, 3030-199 Coimbra, PortugalQuality control of heat sealed bottles is very important to minimize waste and in some cases protect people’s health. The present paper describes a case study where an automated non invasive and non destructive quality control system was designed to assess the quality of the seals of bottles containing pesticide. In this case study, the integrity of the seals is evaluated using an artificial neural network based on images of the seals processed with computer vision techniques. Because the seals are not directly visible from the bottle exterior, the images are infrared pictures obtained using a thermal camera. The method is non invasive, automated, and can be applied to common conveyor belts currently used in industrial plants. The results show that the inspection process is effective in identifying defective seals with a precision of 98.6% and a recall of 100% and because it is automated it can be scaled up to large bottle processing plants.https://www.mdpi.com/2313-433X/7/2/24quality-controlmachine learningcomputer visionthermal imagesartificial neural networks |
spellingShingle | Samuel Cruz António Paulino Joao Duraes Mateus Mendes Real-Time Quality Control of Heat Sealed Bottles Using Thermal Images and Artificial Neural Network Journal of Imaging quality-control machine learning computer vision thermal images artificial neural networks |
title | Real-Time Quality Control of Heat Sealed Bottles Using Thermal Images and Artificial Neural Network |
title_full | Real-Time Quality Control of Heat Sealed Bottles Using Thermal Images and Artificial Neural Network |
title_fullStr | Real-Time Quality Control of Heat Sealed Bottles Using Thermal Images and Artificial Neural Network |
title_full_unstemmed | Real-Time Quality Control of Heat Sealed Bottles Using Thermal Images and Artificial Neural Network |
title_short | Real-Time Quality Control of Heat Sealed Bottles Using Thermal Images and Artificial Neural Network |
title_sort | real time quality control of heat sealed bottles using thermal images and artificial neural network |
topic | quality-control machine learning computer vision thermal images artificial neural networks |
url | https://www.mdpi.com/2313-433X/7/2/24 |
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