Computers and Concrete

  • 제4권3호
  • /
  • Pages.243-257
  • /
  • 2007
  • /
  • 1598-8198(pISSN)
  • /
  • 1598-818X(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

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)
  • 투고 : 2006.09.08
  • 심사 : 2007.07.06
  • 발행 : 2007.06.25
⟨ 이전 논문 다음 논문 ⟩

초록

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%.

키워드

참고문헌

  1. Bettigole, N. and Robison, R. (1997), "Bridge decks: design, construction, rehabilitation, replacement", ASCE press; p. 5.
  2. Carino, N. J. (2003), "Non-destructive test methods to evaluate concrete structures", Proceedings of the 6th CANMET/ACI Int. Conf. on Durability of Concrete, Thessaloniki, Greece, June, 1-78.
  3. Fournier, B. and Berube, M. A. (2000), "Alkali-aggregate reaction in concrete: a review of basic concepts and engineering implications", Canadian J. Civ. Eng., 27, 167-191. https://doi.org/10.1139/l99-072
  4. Fung, T. and Ledrew, E. (1988), "The determination of optimal threshold levels for change detection using various accuracy indices", Photogrammetric Engineering and Remote Sensing, 54(10), 1449-1454.
  5. Gaudreault, M. (2000), "The St. Lawrence Seaway (Quebec, Canada): a case study in the management of structures affected by alkali-aggregate reaction", Proceedings of the 11th Int. Conf. on AAR in Concrete, Quebec City, June, 1293-1302.
  6. Haralick, R. M. (1979), "Statistical and structural approaches to texture", Proceedings of the IEEE, 67(5), 786-804. https://doi.org/10.1109/PROC.1979.11328
  7. Kabir, S., He, D. C. and Rivard, P. (2006), "Urban classification of high resolution IKONOS imagery using texture", Proceedings of Joint Int. Conf. on Computing and Decision Making in Civil and Building Engineering, Montreal, June, 326-335.
  8. Kiema, J. B. K. (2002), "Texture analysis and data fusion in the extraction of topographic objects from satellite imagery", Int. J. Remote Sensing, 23(4), 767-776. https://doi.org/10.1080/01431160010026005
  9. Richards, J. A. and Jia, X. (1999), Remote Sensing Digital Image Analysis: An Introduction, Springer-Verlag, New York.
  10. Rivard, P. and Ballivy, G. (2005), "Assessment of the expansion related to alkali-silica reaction by the damage rating index method", Construction and Building Materials, 19(2), 83-90. https://doi.org/10.1016/j.conbuildmat.2004.06.001
  11. Schowengerdt, R. A. (1997), Remote Sensing: Models and Methods for Image Processing, Academic Press, San Diego.
  12. Scott, M., Rezaizadeh, A., Delahaza, A., Santos, C. G., Moore, M., Graybeal, B. and Washer, G. (2003), "A comparison of nondestructive evaluation methods for bridge deck assessment", NDT&E Int, 36, 245-255. https://doi.org/10.1016/S0963-8695(02)00061-0
  13. Shaban, M. A. and Dikshit, O. (2001), "Improvement of classification in urban areas by the use of textural features: the case study of Lucknow City, Uttar Pradesh", Int. J. Remote Sensing, 22(4), 565-593. https://doi.org/10.1080/01431160050505865

피인용 문헌

  1. Damage assessment for concrete structure using image processing techniques on acoustic borehole imagery vol.23, pp.10, 2009, https://doi.org/10.1016/j.conbuildmat.2009.06.013
  2. Cracks Evaluation of Reinforced Concrete Structure: A Review vol.1783, pp.None, 2007, https://doi.org/10.1088/1742-6596/1783/1/012091