articleIEEE Transactions on Intelligent Transportation SystemsMay 18, 2016Closed access

Automatic Road Crack Detection Using Random Structured Forests

YSYong ShiLCLimeng CuiZQZhiquan QiFMFan MengZCZhen‐Song Chen

University of Nebraska at Omaha · University of Chinese Academy of Sciences · +1 more institution

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Abstract

Cracks are a growing threat to road conditions and have drawn much attention to the construction of intelligent transportation systems. However, as the key part of an intelligent transportation system, automatic road crack detection has been challenged because of the intense inhomogeneity along the cracks, the topology complexity of cracks, the inference of noises with similar texture to the cracks, and so on. In this paper, we propose CrackForest, a novel road crack detection framework based on random structured forests, to address these issues. Our contributions are shown as follows: 1) apply the integral channel features to redefine the tokens that constitute a crack and get better representation of the…

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Topics & keywords

Topics
Keywords
  • Random forest
  • Representation (politics)
  • Computer science
  • Inference
  • Detector
  • Key (lock)
  • Texture (cosmology)
  • Artificial intelligence
UN Sustainable Development Goals
  • Sustainable cities and communities
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