Pavement Crack Detection and Localization using Convolutional Neural Networks (CNNs)

Luqman Ali, Najiya Koderi Valappil, Daniya Najiha Abdul Kareem, Mary Josy John, Hamad Al Jassmi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Citations (Scopus)


Regular inspection and maintenance of roads are required to ensure safe transportation. While examining the state of structural health, cracks are considered as the primary indicators. In the past decades, researchers have been working on various image-based pavement crack detection techniques for non-destructive evaluation. The main advantages of these techniques over manual inspection are accuracy, efficiency and cost. However, the problems associated with the existing methods are their dependence on the handcrafted features, which may not give accurate results due to insufficient feature selection. In this paper, an automatic image-based crack detection algorithm for pavement crack detection using Convolutional Neural Network is proposed. The data set was obtained from various road surfaces of United Arab Emirates (UAE) by using an unmanned aerial vehicles (UAVs) and was used in training and validation of the proposed system. The collected data was also used to create a composite view of the road by creating a continuous mosaic. From the experimental results, it was found that the proposed system has an accuracy of 92% in the validation stage and 90% in the testing stage and can be used for crack detection of road surfaces.

Original languageEnglish
Title of host publicationProceeding of 2019 International Conference on Digitization
Subtitle of host publicationLandscaping Artificial Intelligence, ICD 2019
EditorsManas Ranjan Pradhan, John Senior, Joghee Shanmugan, Omar Hikmat Sattar, Sheikh Abdul Rabik, Beenu Mago
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Electronic)9781728138411
Publication statusPublished - Nov 2019
Event2019 International Conference on Digitization, ICD 2019 - Sharjah, United Arab Emirates
Duration: Nov 18 2019Nov 19 2019

Publication series

NameProceeding of 2019 International Conference on Digitization: Landscaping Artificial Intelligence, ICD 2019


Conference2019 International Conference on Digitization, ICD 2019
Country/TerritoryUnited Arab Emirates


  • Civil Inspection
  • Computer Vision
  • Convolutional Neural Network (CNN)
  • Pavement Crack Detection

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality


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