Fast Blob and Air Line Defects Detection for High Speed Glass Tube Production Lines

During the production of pharmaceutical glass tubes, a machine-vision based inspection system can be utilized to perform the high-quality check required by the process. The necessity to improve detection accuracy, and increase production speed determines the need for fast solutions for defects detec...

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Autores principales:	Gabriele Antonio De Vitis, Antonio Di Tecco, Pierfrancesco Foglia, Cosimo Antonio Prete
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	pharmaceutical glass tube image processing defect detection inspection systems real time inspection Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/19d51b7b57274b35a93f1b20c54f23c1
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id	oai:doaj.org-article:19d51b7b57274b35a93f1b20c54f23c1
record_format	dspace
spelling	oai:doaj.org-article:19d51b7b57274b35a93f1b20c54f23c12021-11-25T18:03:24ZFast Blob and Air Line Defects Detection for High Speed Glass Tube Production Lines10.3390/jimaging71102232313-433Xhttps://doaj.org/article/19d51b7b57274b35a93f1b20c54f23c12021-10-01T00:00:00Zhttps://www.mdpi.com/2313-433X/7/11/223https://doaj.org/toc/2313-433XDuring the production of pharmaceutical glass tubes, a machine-vision based inspection system can be utilized to perform the high-quality check required by the process. The necessity to improve detection accuracy, and increase production speed determines the need for fast solutions for defects detection. Solutions proposed in literature cannot be efficiently exploited due to specific factors that characterize the production process. In this work, we have derived an algorithm that does not change the detection quality compared to state-of-the-art proposals, but does determine a drastic reduction in the processing time. The algorithm utilizes an adaptive threshold based on the Sigma Rule to detect blobs, and applies a threshold to the variation of luminous intensity along a row to detect air lines. These solutions limit the detection effects due to the tube’s curvature, and rotation and vibration of the tube, which characterize glass tube production. The algorithm has been compared with state-of-the-art solutions. The results demonstrate that, with the algorithm proposed, the processing time of the detection phase is reduced by 86%, with an increase in throughput of 268%, achieving greater accuracy in detection. Performance is further improved by adopting Region of Interest reduction techniques. Moreover, we have developed a tuning procedure to determine the algorithm’s parameters in the production batch change. We assessed the performance of the algorithm in a real environment using the “certification” functionality of the machine. Furthermore, we observed that out of 1000 discarded tubes, nine should not have been discarded and a further seven should have been discarded.Gabriele Antonio De VitisAntonio Di TeccoPierfrancesco FogliaCosimo Antonio PreteMDPI AGarticlepharmaceutical glass tubeimage processingdefect detectioninspection systemsreal time inspectionPhotographyTR1-1050Computer applications to medicine. Medical informaticsR858-859.7Electronic computers. Computer scienceQA75.5-76.95ENJournal of Imaging, Vol 7, Iss 223, p 223 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	pharmaceutical glass tube image processing defect detection inspection systems real time inspection Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95
spellingShingle	pharmaceutical glass tube image processing defect detection inspection systems real time inspection Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95 Gabriele Antonio De Vitis Antonio Di Tecco Pierfrancesco Foglia Cosimo Antonio Prete Fast Blob and Air Line Defects Detection for High Speed Glass Tube Production Lines
description	During the production of pharmaceutical glass tubes, a machine-vision based inspection system can be utilized to perform the high-quality check required by the process. The necessity to improve detection accuracy, and increase production speed determines the need for fast solutions for defects detection. Solutions proposed in literature cannot be efficiently exploited due to specific factors that characterize the production process. In this work, we have derived an algorithm that does not change the detection quality compared to state-of-the-art proposals, but does determine a drastic reduction in the processing time. The algorithm utilizes an adaptive threshold based on the Sigma Rule to detect blobs, and applies a threshold to the variation of luminous intensity along a row to detect air lines. These solutions limit the detection effects due to the tube’s curvature, and rotation and vibration of the tube, which characterize glass tube production. The algorithm has been compared with state-of-the-art solutions. The results demonstrate that, with the algorithm proposed, the processing time of the detection phase is reduced by 86%, with an increase in throughput of 268%, achieving greater accuracy in detection. Performance is further improved by adopting Region of Interest reduction techniques. Moreover, we have developed a tuning procedure to determine the algorithm’s parameters in the production batch change. We assessed the performance of the algorithm in a real environment using the “certification” functionality of the machine. Furthermore, we observed that out of 1000 discarded tubes, nine should not have been discarded and a further seven should have been discarded.
format	article
author	Gabriele Antonio De Vitis Antonio Di Tecco Pierfrancesco Foglia Cosimo Antonio Prete
author_facet	Gabriele Antonio De Vitis Antonio Di Tecco Pierfrancesco Foglia Cosimo Antonio Prete
author_sort	Gabriele Antonio De Vitis
title	Fast Blob and Air Line Defects Detection for High Speed Glass Tube Production Lines
title_short	Fast Blob and Air Line Defects Detection for High Speed Glass Tube Production Lines
title_full	Fast Blob and Air Line Defects Detection for High Speed Glass Tube Production Lines
title_fullStr	Fast Blob and Air Line Defects Detection for High Speed Glass Tube Production Lines
title_full_unstemmed	Fast Blob and Air Line Defects Detection for High Speed Glass Tube Production Lines
title_sort	fast blob and air line defects detection for high speed glass tube production lines
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/19d51b7b57274b35a93f1b20c54f23c1
work_keys_str_mv	AT gabrieleantoniodevitis fastblobandairlinedefectsdetectionforhighspeedglasstubeproductionlines AT antonioditecco fastblobandairlinedefectsdetectionforhighspeedglasstubeproductionlines AT pierfrancescofoglia fastblobandairlinedefectsdetectionforhighspeedglasstubeproductionlines AT cosimoantonioprete fastblobandairlinedefectsdetectionforhighspeedglasstubeproductionlines
_version_	1718411665933860864

Fast Blob and Air Line Defects Detection for High Speed Glass Tube Production Lines

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