articleAug 17, 2016Closed access

Road crack detection using deep convolutional neural network

LZLei ZhangFYFan YangYDYimin D. ZhangYJYing Julie Zhu

Temple University

Indexed incrossref

Abstract

Automatic detection of pavement cracks is an important task in transportation maintenance for driving safety assurance. However, it remains a challenging task due to the intensity inhomogeneity of cracks and complexity of the background, e.g., the low contrast with surrounding pavement and possible shadows with similar intensity. Inspired by recent success on applying deep learning to computer vision and medical problems, a deep-learning based method for crack detection is proposed in this paper. A supervised deep convolutional neural network is trained to classify each image patch in the collected images. Quantitative evaluation conducted on a data set of 500 images of size 3264 χ 2448, collected by a…

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Topics & keywords

Topics
Keywords
  • Convolutional neural network
  • Deep learning
  • Computer science
  • Artificial intelligence
  • Task (project management)
  • Set (abstract data type)
  • Deep neural networks
  • Artificial neural network
UN Sustainable Development Goals
  • Sustainable cities and communities
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