Pavement crack analysis by referring to historical crack data based on multi-scale localization

PLoS One. 2020 Aug 14;15(8):e0235171. doi: 10.1371/journal.pone.0235171. eCollection 2020.

Abstract

Pavement crack analysis, which deals with crack detection and crack growth detection, is a crucial task for modern Pavement Management Systems (PMS). This paper proposed a novel approach that uses historical crack data as reference for automatic pavement crack analysis. At first, a multi-scale localization method, which including GPS based coarse localization, image-level localization, and metric localization has been presented to establish image correspondences between historical and query crack images. Then historical crack pixels can be mapped onto the query crack image, and these mapped crack pixels are seen as high-quality seed points for crack analysis. Finally, crack analysis is accomplished by applying Region Growing Method (RGM) to further detect newly grown cracks. The proposed method has been tested with the actual pavement images collected in different time. The F-measure for crack growth is 88.9%, which demonstrates the proposed method has an ability to greatly simplify and enhances crack analysis result.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Construction Materials / standards
  • Materials Science / standards
  • Quality Control*
  • Satellite Imagery / methods*
  • Satellite Imagery / standards
  • Transportation / standards

Grants and funding

The work presented in this paper was funded by the work presented in this paper was funded by the National Natural Science Foundation of China (No.51679181), the Major Project of Technological Innovation in Hubei Province (No.2016AAA007), and the Science-technology Funds for Overseas Chinese Talents of Hubei Province (No.2016-12).