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

Joint Authors

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

Source

Mathematical Problems in Engineering

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-22, 22 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-12-10

Country of Publication

Egypt

No. of Pages

22

Main Subjects

Civil Engineering

Abstract 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.

American Psychological Association (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

Modern Language Association (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

American Medical Association (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

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1201181