CLensRimVision: A Novel Computer Vision Algorithm for Detecting Rim Defects in Contact Lenses
Automated optical inspection (AOI) plays a pivotal role in the quality control of contact lenses, safeguarding the safety and integrity of lenses intended for both medical and cosmetic applications. As the role of computer vision in defect detection expands, our study probes its effectiveness relati...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/23/9610 |
| _version_ | 1797399551032688640 |
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| author | Pawat Chunhachatrachai Chyi-Yeu Lin |
| author_facet | Pawat Chunhachatrachai Chyi-Yeu Lin |
| author_sort | Pawat Chunhachatrachai |
| collection | DOAJ |
| description | Automated optical inspection (AOI) plays a pivotal role in the quality control of contact lenses, safeguarding the safety and integrity of lenses intended for both medical and cosmetic applications. As the role of computer vision in defect detection expands, our study probes its effectiveness relative to traditional methods, particularly concerning subtle and irregular defects on the lens rim. In this research study, we propose a novel algorithm designed for the precise and automated detection of rim defects in contact lenses called “CLensRimVision”. This algorithm integrates a series of procedures, including image preprocessing, circle detection for identifying lens rims, polar coordinate transformation, setting defect criteria and their subsequent detection, and, finally, visualization. The method based on these criteria can be adapted either to thickness-based or area-based approaches, suiting various characteristics of the contact lens. This approach achieves an exemplary performance with a 0.937 AP score. Our results offer a richer understanding of defect detection strategies, guiding manufacturers and researchers towards optimal techniques for ensuring quality in the contact lens domain. |
| first_indexed | 2024-03-09T01:41:49Z |
| format | Article |
| id | doaj.art-2b439ba0f9ce49ccb24fa08d1b3784ca |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T01:41:49Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2b439ba0f9ce49ccb24fa08d1b3784ca2023-12-08T15:26:34ZengMDPI AGSensors1424-82202023-12-012323961010.3390/s23239610CLensRimVision: A Novel Computer Vision Algorithm for Detecting Rim Defects in Contact LensesPawat Chunhachatrachai0Chyi-Yeu Lin1Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10632, TaiwanDepartment of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10632, TaiwanAutomated optical inspection (AOI) plays a pivotal role in the quality control of contact lenses, safeguarding the safety and integrity of lenses intended for both medical and cosmetic applications. As the role of computer vision in defect detection expands, our study probes its effectiveness relative to traditional methods, particularly concerning subtle and irregular defects on the lens rim. In this research study, we propose a novel algorithm designed for the precise and automated detection of rim defects in contact lenses called “CLensRimVision”. This algorithm integrates a series of procedures, including image preprocessing, circle detection for identifying lens rims, polar coordinate transformation, setting defect criteria and their subsequent detection, and, finally, visualization. The method based on these criteria can be adapted either to thickness-based or area-based approaches, suiting various characteristics of the contact lens. This approach achieves an exemplary performance with a 0.937 AP score. Our results offer a richer understanding of defect detection strategies, guiding manufacturers and researchers towards optimal techniques for ensuring quality in the contact lens domain.https://www.mdpi.com/1424-8220/23/23/9610contact lenscomputer visionautomatic optical inspectiondefect detectionimage processing |
| spellingShingle | Pawat Chunhachatrachai Chyi-Yeu Lin CLensRimVision: A Novel Computer Vision Algorithm for Detecting Rim Defects in Contact Lenses Sensors contact lens computer vision automatic optical inspection defect detection image processing |
| title | CLensRimVision: A Novel Computer Vision Algorithm for Detecting Rim Defects in Contact Lenses |
| title_full | CLensRimVision: A Novel Computer Vision Algorithm for Detecting Rim Defects in Contact Lenses |
| title_fullStr | CLensRimVision: A Novel Computer Vision Algorithm for Detecting Rim Defects in Contact Lenses |
| title_full_unstemmed | CLensRimVision: A Novel Computer Vision Algorithm for Detecting Rim Defects in Contact Lenses |
| title_short | CLensRimVision: A Novel Computer Vision Algorithm for Detecting Rim Defects in Contact Lenses |
| title_sort | clensrimvision a novel computer vision algorithm for detecting rim defects in contact lenses |
| topic | contact lens computer vision automatic optical inspection defect detection image processing |
| url | https://www.mdpi.com/1424-8220/23/23/9610 |
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