Pavement Crack Detection and Segmentation Method Based on Improved Deep Learning Fusion Model

المؤلفون المشاركون

Shen, Hao
Sun, Zhaoyun
Feng, Xiaoran
Xiao, Liyang
Pei, Lili
Ma, Zhidan
Ju, Huyan
Li, Wei

المصدر

Mathematical Problems in Engineering

العدد

المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-22، 22ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2020-12-10

دولة النشر

مصر

عدد الصفحات

22

التخصصات الرئيسية

هندسة مدنية

الملخص EN

Pavement damage is the main factor affecting road performance.

Pavement cracking, a common type of road damage, is a key challenge in road maintenance.

In order to achieve an accurate crack classification, segmentation, and geometric parameter calculation, this paper proposes a method based on a deep convolutional neural network fusion model for pavement crack identification, which combines the advantages of the multitarget single-shot multibox detector (SSD) convolutional neural network model and the U-Net model.

First, the crack classification and detection model is applied to classify the cracks and obtain the detection confidence.

Next, the crack segmentation network is applied to accurately segment the pavement cracks.

By improving the feature extraction structure and optimizing the hyperparameters of the model, pavement crack classification and segmentation accuracy were improved.

Finally, the length and width (for linear cracks) and the area (for alligator cracks) are calculated according to the segmentation results.

Test results show that the recognition accuracy of the pavement crack identification method for transverse, longitudinal, and alligator cracks is 86.8%, 87.6%, and 85.5%, respectively.

It is demonstrated that the proposed method can provide the category information for pavement cracks as well as the accurate positioning and geometric parameter information, which can be used directly for evaluating the pavement condition.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Feng, Xiaoran& Xiao, Liyang& Li, Wei& Pei, Lili& Sun, Zhaoyun& Shen, Hao…[et al.]. 2020. Pavement Crack Detection and Segmentation Method Based on Improved Deep Learning Fusion Model. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-22.
https://search.emarefa.net/detail/BIM-1201181

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Li, Wei…[et al.]. Pavement Crack Detection and Segmentation Method Based on Improved Deep Learning Fusion Model. Mathematical Problems in Engineering No. 2020 (2020), pp.1-22.
https://search.emarefa.net/detail/BIM-1201181

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Feng, Xiaoran& Xiao, Liyang& Li, Wei& Pei, Lili& Sun, Zhaoyun& Shen, Hao…[et al.]. Pavement Crack Detection and Segmentation Method Based on Improved Deep Learning Fusion Model. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-22.
https://search.emarefa.net/detail/BIM-1201181

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1201181