Implementing Image Processing for Quality Inspection of Car Air Conditioning Vents
Quality inspection in the manufacturing of car air conditioning vents has traditionally relied on human operators, a process prone to subjectivity, inconsistency, and inefficiency due to factors like fatigue and human error. To overcome these limitations, this study proposes an automated quality ins...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-02-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/84/1/46 |
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| author | Hong Zhuang Yuan Kamarul Hawari Ghazali Adyanata Lubis Sunardi Sunardi Budi Yanto Samra Urooj Khan |
| author_facet | Hong Zhuang Yuan Kamarul Hawari Ghazali Adyanata Lubis Sunardi Sunardi Budi Yanto Samra Urooj Khan |
| author_sort | Hong Zhuang Yuan |
| collection | DOAJ |
| description | Quality inspection in the manufacturing of car air conditioning vents has traditionally relied on human operators, a process prone to subjectivity, inconsistency, and inefficiency due to factors like fatigue and human error. To overcome these limitations, this study proposes an automated quality inspection system using image processing techniques to detect defects such as missing parts and scratches. Using MATLAB, the system integrates image acquisition, enhancement, segmentation, and defect analysis for consistent and accurate inspection. Images are captured under controlled lighting with optimal camera positioning to minimize distortion, and preprocessing techniques such as contrast adjustment, morphological operations, and adaptive thresholding are applied to refine image quality and highlight defects. Extensive validation of the system demonstrated over 90% accuracy in defect detection, particularly when vent positions and angles were fixed. This study highlights the potential of combining image processing and machine vision to improve quality control processes in the automotive industry, offering a reliable alternative to traditional manual inspections. |
| format | Article |
| id | doaj-art-af7fc45a04f24bca9de6c7b3b160543e |
| institution | Kabale University |
| issn | 2673-4591 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-af7fc45a04f24bca9de6c7b3b160543e2025-08-20T03:27:18ZengMDPI AGEngineering Proceedings2673-45912025-02-018414610.3390/engproc2025084046Implementing Image Processing for Quality Inspection of Car Air Conditioning VentsHong Zhuang Yuan0Kamarul Hawari Ghazali1Adyanata Lubis2Sunardi Sunardi3Budi Yanto4Samra Urooj Khan5Faculty of Electrical and Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan Pahang 26600, MalaysiaFaculty of Electrical and Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan Pahang 26600, MalaysiaDepartment of Computers Science, Universitas Rokania, Langkitin, Rambah Samo, Rokan Hulu Regency 28557, Riau, IndonesiaDepartment of Electrical Engineering, Universitas Ahmad Dahlan, Yogyakarta 55191, Special Region of Yogyakarta, IndonesiaDepartment of Computer Science, Universitas Pasir Pengaraian, Jl. Tuanku Tambusai, Jl. Raya Kumu, Rambah, Kec. Rambah Hilir, Kabupaten Rokan Hulu 28558, Riau, IndonesiaFaculty of Electrical and Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan Pahang 26600, MalaysiaQuality inspection in the manufacturing of car air conditioning vents has traditionally relied on human operators, a process prone to subjectivity, inconsistency, and inefficiency due to factors like fatigue and human error. To overcome these limitations, this study proposes an automated quality inspection system using image processing techniques to detect defects such as missing parts and scratches. Using MATLAB, the system integrates image acquisition, enhancement, segmentation, and defect analysis for consistent and accurate inspection. Images are captured under controlled lighting with optimal camera positioning to minimize distortion, and preprocessing techniques such as contrast adjustment, morphological operations, and adaptive thresholding are applied to refine image quality and highlight defects. Extensive validation of the system demonstrated over 90% accuracy in defect detection, particularly when vent positions and angles were fixed. This study highlights the potential of combining image processing and machine vision to improve quality control processes in the automotive industry, offering a reliable alternative to traditional manual inspections.https://www.mdpi.com/2673-4591/84/1/46automated quality inspectionimage processing for defect detectioncar air con vent inspection |
| spellingShingle | Hong Zhuang Yuan Kamarul Hawari Ghazali Adyanata Lubis Sunardi Sunardi Budi Yanto Samra Urooj Khan Implementing Image Processing for Quality Inspection of Car Air Conditioning Vents Engineering Proceedings automated quality inspection image processing for defect detection car air con vent inspection |
| title | Implementing Image Processing for Quality Inspection of Car Air Conditioning Vents |
| title_full | Implementing Image Processing for Quality Inspection of Car Air Conditioning Vents |
| title_fullStr | Implementing Image Processing for Quality Inspection of Car Air Conditioning Vents |
| title_full_unstemmed | Implementing Image Processing for Quality Inspection of Car Air Conditioning Vents |
| title_short | Implementing Image Processing for Quality Inspection of Car Air Conditioning Vents |
| title_sort | implementing image processing for quality inspection of car air conditioning vents |
| topic | automated quality inspection image processing for defect detection car air con vent inspection |
| url | https://www.mdpi.com/2673-4591/84/1/46 |
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