SCUNet structured flowchart.
<div><p>In recent years, the demand for efficient and accurate defect detection algorithms in industrial production has been increasing. However, industrial cameras may be affected by water fog during image acquisition, resulting in image blurring and quality degradation, which increases...
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2025
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| _version_ | 1852020814782660608 |
|---|---|
| author | Xuanyi Zhao (5896112) |
| author2 | Xiaohan Dou (17142896) Gengpei Zhang (10131572) |
| author2_role | author author |
| author_facet | Xuanyi Zhao (5896112) Xiaohan Dou (17142896) Gengpei Zhang (10131572) |
| author_role | author |
| dc.creator.none.fl_str_mv | Xuanyi Zhao (5896112) Xiaohan Dou (17142896) Gengpei Zhang (10131572) |
| dc.date.none.fl_str_mv | 2025-05-02T17:37:50Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0322217.g003 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/SCUNet_structured_flowchart_/28922985 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Sociology Developmental Biology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified offers valuable references novel technical approach experimental results show industrial cameras may enhance detection performance object detection tasks water fog achieves industrial defect detection industrial images affected image processing technique defect detection water fog industrial production image processing rescue tasks image blurring image acquisition xlink "> study provides smoke environments research indicates recent years quality degradation personnel localization paper proposes madnet models complex environments average psnr 9 db |
| dc.title.none.fl_str_mv | SCUNet structured flowchart. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <div><p>In recent years, the demand for efficient and accurate defect detection algorithms in industrial production has been increasing. However, industrial cameras may be affected by water fog during image acquisition, resulting in image blurring and quality degradation, which increases the difficulty of defect detection. This paper proposes an industrial defect detection algorithm incorporating dehazing technology to enhance detection performance in complex environments. Experimental results show that using an optimized dehazing processing method on industrial images affected by water fog achieves an average PSNR of 34.9 dB and an SSIM of 0.951. The overall performance surpasses CNN and MADNet models, and verification using the improved YOLOv8 model significantly enhances defect detection confidence while greatly reducing missed detections. Further research indicates that this method is not only applicable to industrial defect detection but can also be transferred to personnel localization and rescue tasks in fire and smoke environments. This study provides a novel technical approach for industrial defect detection in complex environments and offers valuable references for image processing and object detection tasks in other fields.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_14aaedccf0b07f8cef684ff2a9869256 |
| identifier_str_mv | 10.1371/journal.pone.0322217.g003 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28922985 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | SCUNet structured flowchart.Xuanyi Zhao (5896112)Xiaohan Dou (17142896)Gengpei Zhang (10131572)SociologyDevelopmental BiologySpace ScienceEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedoffers valuable referencesnovel technical approachexperimental results showindustrial cameras mayenhance detection performanceobject detection taskswater fog achievesindustrial defect detectionindustrial images affectedimage processing techniquedefect detectionwater fogindustrial productionimage processingrescue tasksimage blurringimage acquisitionxlink ">study providessmoke environmentsresearch indicatesrecent yearsquality degradationpersonnel localizationpaper proposesmadnet modelscomplex environmentsaverage psnr9 db<div><p>In recent years, the demand for efficient and accurate defect detection algorithms in industrial production has been increasing. However, industrial cameras may be affected by water fog during image acquisition, resulting in image blurring and quality degradation, which increases the difficulty of defect detection. This paper proposes an industrial defect detection algorithm incorporating dehazing technology to enhance detection performance in complex environments. Experimental results show that using an optimized dehazing processing method on industrial images affected by water fog achieves an average PSNR of 34.9 dB and an SSIM of 0.951. The overall performance surpasses CNN and MADNet models, and verification using the improved YOLOv8 model significantly enhances defect detection confidence while greatly reducing missed detections. Further research indicates that this method is not only applicable to industrial defect detection but can also be transferred to personnel localization and rescue tasks in fire and smoke environments. This study provides a novel technical approach for industrial defect detection in complex environments and offers valuable references for image processing and object detection tasks in other fields.</p></div>2025-05-02T17:37:50ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0322217.g003https://figshare.com/articles/figure/SCUNet_structured_flowchart_/28922985CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/289229852025-05-02T17:37:50Z |
| spellingShingle | SCUNet structured flowchart. Xuanyi Zhao (5896112) Sociology Developmental Biology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified offers valuable references novel technical approach experimental results show industrial cameras may enhance detection performance object detection tasks water fog achieves industrial defect detection industrial images affected image processing technique defect detection water fog industrial production image processing rescue tasks image blurring image acquisition xlink "> study provides smoke environments research indicates recent years quality degradation personnel localization paper proposes madnet models complex environments average psnr 9 db |
| status_str | publishedVersion |
| title | SCUNet structured flowchart. |
| title_full | SCUNet structured flowchart. |
| title_fullStr | SCUNet structured flowchart. |
| title_full_unstemmed | SCUNet structured flowchart. |
| title_short | SCUNet structured flowchart. |
| title_sort | SCUNet structured flowchart. |
| topic | Sociology Developmental Biology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified offers valuable references novel technical approach experimental results show industrial cameras may enhance detection performance object detection tasks water fog achieves industrial defect detection industrial images affected image processing technique defect detection water fog industrial production image processing rescue tasks image blurring image acquisition xlink "> study provides smoke environments research indicates recent years quality degradation personnel localization paper proposes madnet models complex environments average psnr 9 db |