Computer-Vision-Based Product Quality Inspection and Novel Counting System
In this study, we aimed to enhance the accuracy of product quality inspection and counting in the manufacturing process by integrating image processing and human body detection algorithms. We employed the SIFT algorithm combined with traditional image comparison metrics such as SSIM, PSNR, and MSE t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Applied System Innovation |
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| Online Access: | https://www.mdpi.com/2571-5577/7/6/127 |
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| author | Changhyun Lee Yunsik Kim Hunkee Kim |
| author_facet | Changhyun Lee Yunsik Kim Hunkee Kim |
| author_sort | Changhyun Lee |
| collection | DOAJ |
| description | In this study, we aimed to enhance the accuracy of product quality inspection and counting in the manufacturing process by integrating image processing and human body detection algorithms. We employed the SIFT algorithm combined with traditional image comparison metrics such as SSIM, PSNR, and MSE to develop a defect detection system that is robust against variations in rotation and scale. Additionally, the YOLOv8 Pose algorithm was used to detect and correct errors in product counting caused by human interference on the load cell in real time. By applying the image differencing technique, we accurately calculated the unit weight of products and determined their total count. In our experiments conducted on products weighing over 1 kg, we achieved a high accuracy of 99.268%. The integration of our algorithms with the load-cell-based counting system demonstrates reliable real-time quality inspection and automated counting in manufacturing environments. |
| format | Article |
| id | doaj-art-c9bfb6a1edbc4f959f40bdd89c74dd72 |
| institution | DOAJ |
| issn | 2571-5577 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied System Innovation |
| spelling | doaj-art-c9bfb6a1edbc4f959f40bdd89c74dd722025-08-20T02:55:54ZengMDPI AGApplied System Innovation2571-55772024-12-017612710.3390/asi7060127Computer-Vision-Based Product Quality Inspection and Novel Counting SystemChanghyun Lee0Yunsik Kim1Hunkee Kim2AI System Lab, Department of Advanced Materials Processing Engineering, Inha University, 36 Gaetbeol-ro, Yeonsu-gu, Incheon 21999, Republic of KoreaAI System Lab, Department of Advanced Materials Processing Engineering, Inha University, 36 Gaetbeol-ro, Yeonsu-gu, Incheon 21999, Republic of KoreaAI System Lab, Department of Advanced Materials Processing Engineering, Inha University, 36 Gaetbeol-ro, Yeonsu-gu, Incheon 21999, Republic of KoreaIn this study, we aimed to enhance the accuracy of product quality inspection and counting in the manufacturing process by integrating image processing and human body detection algorithms. We employed the SIFT algorithm combined with traditional image comparison metrics such as SSIM, PSNR, and MSE to develop a defect detection system that is robust against variations in rotation and scale. Additionally, the YOLOv8 Pose algorithm was used to detect and correct errors in product counting caused by human interference on the load cell in real time. By applying the image differencing technique, we accurately calculated the unit weight of products and determined their total count. In our experiments conducted on products weighing over 1 kg, we achieved a high accuracy of 99.268%. The integration of our algorithms with the load-cell-based counting system demonstrates reliable real-time quality inspection and automated counting in manufacturing environments.https://www.mdpi.com/2571-5577/7/6/127SIFT algorithmimage-based quality inspectionproduct countingYOLOv8 Poseload cellfeature matching |
| spellingShingle | Changhyun Lee Yunsik Kim Hunkee Kim Computer-Vision-Based Product Quality Inspection and Novel Counting System Applied System Innovation SIFT algorithm image-based quality inspection product counting YOLOv8 Pose load cell feature matching |
| title | Computer-Vision-Based Product Quality Inspection and Novel Counting System |
| title_full | Computer-Vision-Based Product Quality Inspection and Novel Counting System |
| title_fullStr | Computer-Vision-Based Product Quality Inspection and Novel Counting System |
| title_full_unstemmed | Computer-Vision-Based Product Quality Inspection and Novel Counting System |
| title_short | Computer-Vision-Based Product Quality Inspection and Novel Counting System |
| title_sort | computer vision based product quality inspection and novel counting system |
| topic | SIFT algorithm image-based quality inspection product counting YOLOv8 Pose load cell feature matching |
| url | https://www.mdpi.com/2571-5577/7/6/127 |
| work_keys_str_mv | AT changhyunlee computervisionbasedproductqualityinspectionandnovelcountingsystem AT yunsikkim computervisionbasedproductqualityinspectionandnovelcountingsystem AT hunkeekim computervisionbasedproductqualityinspectionandnovelcountingsystem |