An investigation on smartphone based machine vision system for inspection
Machine vision system for inspection is an automated technology that is normally utilized to analyse items on the production line for quality control purposes, it also can be known as automated visual inspection (AVI) system. By applying automated visual inspection, the existence of items, defects,...
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| Format: | Final Year Project / Dissertation / Thesis |
| Published: |
2022
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| Online Access: | http://eprints.utar.edu.my/5392/ http://eprints.utar.edu.my/5392/1/MH_1703177_Final_%2D_SHAO_PENG_THEY.pdf |
| _version_ | 1848886403806527488 |
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| author | They, Shao Peng |
| author_facet | They, Shao Peng |
| author_sort | They, Shao Peng |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | Machine vision system for inspection is an automated technology that is normally utilized to analyse items on the production line for quality control purposes, it also can be known as automated visual inspection (AVI) system. By applying automated visual inspection, the existence of items, defects, contaminants, flaws and other irregularities in manufactured products can be easily detected in a short time and accurately. However, AVI systems are still inflexible and expensive due to their uniqueness for a specific task and consuming a lot of set-up time and space. With the rapid development of mobile devices, smartphones can be an alternative device for the visual system to solve the existing problems of AVI. Since the smartphone-based AVI system is still at a nascent stage, this led to the motivation to investigate the smartphone-based AVI system. This study is aimed to provide a low-cost AVI system with high efficiency and flexibility. In this project, the object detection models which are You Only Look Once (YOLO) model and Single Shot MultiBox Detector (SSD) model are trained, evaluated and integrated with the smartphone and webcam devices. The performance of the smartphone-based AVI is compared with the webcam-based AVI according to the precision and inference time in this study. Additionally, a mobile application is developed which allows users to implement real-time object detection and object detection from image storage. |
| first_indexed | 2025-11-15T19:37:57Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-5392 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:37:57Z |
| publishDate | 2022 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-53922023-06-16T14:26:30Z An investigation on smartphone based machine vision system for inspection They, Shao Peng TJ Mechanical engineering and machinery Machine vision system for inspection is an automated technology that is normally utilized to analyse items on the production line for quality control purposes, it also can be known as automated visual inspection (AVI) system. By applying automated visual inspection, the existence of items, defects, contaminants, flaws and other irregularities in manufactured products can be easily detected in a short time and accurately. However, AVI systems are still inflexible and expensive due to their uniqueness for a specific task and consuming a lot of set-up time and space. With the rapid development of mobile devices, smartphones can be an alternative device for the visual system to solve the existing problems of AVI. Since the smartphone-based AVI system is still at a nascent stage, this led to the motivation to investigate the smartphone-based AVI system. This study is aimed to provide a low-cost AVI system with high efficiency and flexibility. In this project, the object detection models which are You Only Look Once (YOLO) model and Single Shot MultiBox Detector (SSD) model are trained, evaluated and integrated with the smartphone and webcam devices. The performance of the smartphone-based AVI is compared with the webcam-based AVI according to the precision and inference time in this study. Additionally, a mobile application is developed which allows users to implement real-time object detection and object detection from image storage. 2022 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/5392/1/MH_1703177_Final_%2D_SHAO_PENG_THEY.pdf They, Shao Peng (2022) An investigation on smartphone based machine vision system for inspection. Final Year Project, UTAR. http://eprints.utar.edu.my/5392/ |
| spellingShingle | TJ Mechanical engineering and machinery They, Shao Peng An investigation on smartphone based machine vision system for inspection |
| title | An investigation on smartphone based machine vision system for inspection |
| title_full | An investigation on smartphone based machine vision system for inspection |
| title_fullStr | An investigation on smartphone based machine vision system for inspection |
| title_full_unstemmed | An investigation on smartphone based machine vision system for inspection |
| title_short | An investigation on smartphone based machine vision system for inspection |
| title_sort | investigation on smartphone based machine vision system for inspection |
| topic | TJ Mechanical engineering and machinery |
| url | http://eprints.utar.edu.my/5392/ http://eprints.utar.edu.my/5392/1/MH_1703177_Final_%2D_SHAO_PENG_THEY.pdf |