Cracks in bridge floor detected by 2-dimensional complex discrete wavelet packet transform

Zhong Zhang, Ohzora Hamata, Takuma Akiduki, Tomoaki Mashimo, Taiki Saito, Kazuhiro Hayashi

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Bridge inspection is usually done visually on-site, and for this reason is problematic in places inaccessible to inspectors. In this paper we propose a solution through the analysis of features in captured images that suggest potential problems. We focus on the ability to detect cracks, and a complex-valued Haar wavelet is designed and applied to a 2D-CWPT, which is then combined with an anisotropic diffusion filter. A detection method for linear cracks is proposed through interpolation of the crack loss area and extraction processing according to the shape feature. The main results are: 1) we confirm that the complex-valued Haar wavelet is more effective for edge enhancement than the complex-valued Meyer wavelet; 2) quantitative evaluation of the proposed method for crack detection using the correct rate, sensitivity, specificity, precision rate, and F-value confirms the effectiveness of the method.

Original languageEnglish
Pages (from-to)2007-2019
Number of pages13
JournalInternational Journal of Innovative Computing, Information and Control
Issue number6
Publication statusPublished - 2020
Externally publishedYes


  • 2D-CWPT
  • Complex-valued Haar wavelet
  • Crack
  • Feature extraction
  • Fre-quency analysis
  • Image processing

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Computational Theory and Mathematics


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