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Abstract: With the increasing utilization of plastic bottles in the fast-moving consumer goods industry, the efficiency and accuracy of the bottle defect inspection process becomes very important for quality assurance. Deep-learning-based inspection is accurate and robust, but at the same time data hogging and computationally expensive. Thus, it is not feasible for fast inspection. Therefore, this paper presents an efficient and fast machine-vision-based system for inspecting plastic bottle defects. The system is composed of a chamber which has a camera and illuminators to capture high-resolution images in controlled lighting conditions. Captured images are processed by using simple image processing techniques to identify multiple defects such as seated cap, dents on the body and label alignment on the plastic. The experimental results show that the proposed system is 95% accurate in determining a range of bottle defects. It is highly feasible for fast inspection and does not require high computation power and a large amount of training data. Keywords: quality assurance; inspection system; plastic bottle defects; digital image processing

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Kazmi, M., Hafeez, B., Khan, H. R., & Qazi, S. A. (2022). Machine-Vision-Based Plastic Bottle Inspection for Quality Assurance. Engineering Proceedings, 20(1), 9. https://doi.org/10.3390/engproc2022020009

Kazmi M, Hafeez B, Khan HR, Qazi SA. Machine-Vision-Based Plastic Bottle Inspection for Quality Assurance. Engineering Proceedings. 2022; 20(1):9. https://doi.org/10.3390/engproc2022020009

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Kazmi, Majida, Basra Hafeez, Hashim Raza Khan, and Saad Ahmed Qazi. 2022. "Machine-Vision-Based Plastic Bottle Inspection for Quality Assurance" Engineering Proceedings 20, no. 1: 9. https://doi.org/10.3390/engproc2022020009

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Kazmi M, Hafeez B, Khan HR, Qazi SA. Machine-Vision-Based Plastic Bottle Inspection for Quality Assurance. Engineering Proceedings. 2022; 20(1):9. https://doi.org/10.3390/engproc2022020009

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

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Kazmi, Majida, Basra Hafeez, Hashim Raza Khan, and Saad Ahmed Qazi. 2022. "Machine-Vision-Based Plastic Bottle Inspection for Quality Assurance" Engineering Proceedings 20, no. 1: 9. https://doi.org/10.3390/engproc2022020009

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Kazmi, M.; Hafeez, B.; Khan, H.R.; Qazi, S.A. Machine-Vision-Based Plastic Bottle Inspection for Quality Assurance. Eng. Proc. 2022, 20, 9. https://doi.org/10.3390/engproc2022020009

Kazmi, M., Hafeez, B., Khan, H. R., & Qazi, S. A. (2022). Machine-Vision-Based Plastic Bottle Inspection for Quality Assurance. Engineering Proceedings, 20(1), 9. https://doi.org/10.3390/engproc2022020009

Kazmi, M.; Hafeez, B.; Khan, H.R.; Qazi, S.A. Machine-Vision-Based Plastic Bottle Inspection for Quality Assurance. Eng. Proc. 2022, 20, 9. https://doi.org/10.3390/engproc2022020009

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.