Deep Learning-based Pavement Cracks Detection via Wireless Visible Light Camera-based Network

Yuxin Zou, Wen Cao, Mingyuan Luo, Peng Zhang, Wei Wang, Wei Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Road maintenance is important to ensure the normal usage of road transportation. Due to complicated effects including natural consumptions and human overuses, various forms of damages appear on the road surface, and among them, pavement cracks are the most representative ones. Therefore, the automatic detection of pavement cracks is important and essential in road maintenance. In this study, deep learning techniques are incorporated to fulfill the automatic pavement cracks detection based on a wireless visible light camera-based network. Technically, a visible light high-definition camera is equipped at the bottom of a maintenance vehicle, and pavement images are automatically captured along with the movement of the vehicle. Then, images are wirelessly transferred to a workstation on the maintenance vehicle, and the pavement cracks detection task is fulfilled via deep learning techniques from the classification perspective. Experimental results demonstrate that, the above wireless visible light camera-based system is capable to discern pavement cracks accurately. Also, real-time performance is guaranteed within this deep learning-based pavement cracks detection study.

Original languageEnglish
Title of host publication2019 Computing, Communications and IoT Applications, ComComAp 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages47-52
Number of pages6
ISBN (Electronic)9781728119731
DOIs
StatePublished - Oct 2019
Event2019 IEEE International Conference on Computing, Communications and IoT Applications, ComComAp 2019 - Shenzhen, China
Duration: 26 Oct 201928 Oct 2019

Publication series

Name2019 Computing, Communications and IoT Applications, ComComAp 2019

Conference

Conference2019 IEEE International Conference on Computing, Communications and IoT Applications, ComComAp 2019
Country/TerritoryChina
CityShenzhen
Period26/10/1928/10/19

Keywords

  • Deep Learning
  • Detection
  • Wireless Network

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