Automated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment

Pavement cracks are severely affecting highway performance. Thus, implementing high-precision highway pavement crack detection is important for highway maintenance. However, the asphalt highway pavement environment is complex, and different pavement backgrounds are more difficult than others for det...

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Autores principales:	Kun Yan, Zhihua Zhang
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Crack detection deformable convolution multi-scale SSD Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/cd4f544206254b87b12f025f235f2e8a
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id	oai:doaj.org-article:cd4f544206254b87b12f025f235f2e8a
record_format	dspace
spelling	oai:doaj.org-article:cd4f544206254b87b12f025f235f2e8a2021-11-18T00:07:12ZAutomated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment2169-353610.1109/ACCESS.2021.3125703https://doaj.org/article/cd4f544206254b87b12f025f235f2e8a2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9605622/https://doaj.org/toc/2169-3536Pavement cracks are severely affecting highway performance. Thus, implementing high-precision highway pavement crack detection is important for highway maintenance. However, the asphalt highway pavement environment is complex, and different pavement backgrounds are more difficult than others for detecting highway pavement cracks. Interference from road markings and surface repairs also complicate the environments and thus the detection of crack. To reduce interference, we collected many images from different highway pavement backgrounds. We also improved the single shot multi-box detector (SSD) network and proposed a novel network named deformable SSD by adding a deformable convolution to the backbone feature extraction network VGG16. We verified our model using the PASCAL VOC2007 dataset and obtained a mean average precision (<italic>mAP</italic>) 3.1% higher than that of the original SSD model. We then trained and tested the proposed model using our crack detection dataset. We calculated precision, recall, F1 score, AP, <italic>mAP</italic>, and FPS to examine the performance of our model. The <italic>mAP</italic> of all categories in the test data was 85.11% using the proposed model 10.4% and 0.55% more than that of YOLOv4 and the original SSD model, respectively. These findings show that our model outperforms YOLOv4 and the original SSD model and confirm that incorporating a deformable convolution into the SSD network can improve the model’s performance. The proposed model is appropriate for detecting pavement crack categories and locations in complicated environments. It can also provide important technical support for highway maintenance.Kun YanZhihua ZhangIEEEarticleCrack detectiondeformable convolutionmulti-scaleSSDElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 150925-150938 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Crack detection deformable convolution multi-scale SSD Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Crack detection deformable convolution multi-scale SSD Electrical engineering. Electronics. Nuclear engineering TK1-9971 Kun Yan Zhihua Zhang Automated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment
description	Pavement cracks are severely affecting highway performance. Thus, implementing high-precision highway pavement crack detection is important for highway maintenance. However, the asphalt highway pavement environment is complex, and different pavement backgrounds are more difficult than others for detecting highway pavement cracks. Interference from road markings and surface repairs also complicate the environments and thus the detection of crack. To reduce interference, we collected many images from different highway pavement backgrounds. We also improved the single shot multi-box detector (SSD) network and proposed a novel network named deformable SSD by adding a deformable convolution to the backbone feature extraction network VGG16. We verified our model using the PASCAL VOC2007 dataset and obtained a mean average precision (<italic>mAP</italic>) 3.1% higher than that of the original SSD model. We then trained and tested the proposed model using our crack detection dataset. We calculated precision, recall, F1 score, AP, <italic>mAP</italic>, and FPS to examine the performance of our model. The <italic>mAP</italic> of all categories in the test data was 85.11% using the proposed model 10.4% and 0.55% more than that of YOLOv4 and the original SSD model, respectively. These findings show that our model outperforms YOLOv4 and the original SSD model and confirm that incorporating a deformable convolution into the SSD network can improve the model’s performance. The proposed model is appropriate for detecting pavement crack categories and locations in complicated environments. It can also provide important technical support for highway maintenance.
format	article
author	Kun Yan Zhihua Zhang
author_facet	Kun Yan Zhihua Zhang
author_sort	Kun Yan
title	Automated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment
title_short	Automated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment
title_full	Automated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment
title_fullStr	Automated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment
title_full_unstemmed	Automated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment
title_sort	automated asphalt highway pavement crack detection based on deformable single shot multi-box detector under a complex environment
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/cd4f544206254b87b12f025f235f2e8a
work_keys_str_mv	AT kunyan automatedasphalthighwaypavementcrackdetectionbasedondeformablesingleshotmultiboxdetectorunderacomplexenvironment AT zhihuazhang automatedasphalthighwaypavementcrackdetectionbasedondeformablesingleshotmultiboxdetectorunderacomplexenvironment
_version_	1718425251486892032

Automated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment

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