Computers and Concrete

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Damage classification of concrete structures based on grey level co-occurrence matrix using Haar's discrete wavelet transform

  • Kabir, Shahid (Groupe de Recherche sur l'Auscultation et l'Instrumentation (GRAI), Department of Civil Enginering, Universite de Sherbriike) ;
  • Rivard, Patrice (Groupe de Recherche sur l'Auscultation et l'Instrumentation (GRAI), Department of Civil Enginering, Universite de Sherbriike)
  • Received : 2006.09.08
  • Accepted : 2007.07.06
  • Published : 2007.06.25
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Abstract

A novel method for recognition, characterization, and quantification of deterioration in bridge components and laboratory concrete samples is presented in this paper. The proposed scheme is based on grey level co-occurrence matrix texture analysis using Haar's discrete wavelet transform on concrete imagery. Each image is described by a subset of band-filtered images containing wavelet coefficients, and then reconstructed images are employed in characterizing the texture, using grey level co-occurrence matrices, of the different types and degrees of damage: map-cracking, spalling and steel corrosion. A comparative study was conducted to evaluate the efficiency of the supervised maximum likelihood and unsupervised K-means classification techniques, in order to classify and quantify the deterioration and its extent. Experimental results show both methods are relatively effective in characterizing and quantifying damage; however, the supervised technique produced more accurate results, with overall classification accuracies ranging from 76.8% to 79.1%.

Keywords

References

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