[go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Recognition of Concrete Surface Cracks Using ART2-Based Radial Basis Function Neural Network

  • Conference paper
Computational Science and Its Applications - ICCSA 2006 (ICCSA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3982))

Included in the following conference series:

  • 1461 Accesses

Abstract

In this paper, we proposed the image processing techniques for extracting the cracks in a concrete surface crack image and the ART2-based radial basis function neural network for recognizing the directions of the extracted cracks. The image processing techniques used are the closing operation of morphological techniques, the Sobel masking used to extract edges of the cracks, and the iterated binarization for acquiring the binarized image from the crack image. The cracks are extracted from the concrete surface image after applying two times of noise reduction to the binarized image. We proposed the method for automatically recognizing the directions (horizontal, vertical, -45 degree, 45 direction degree) of the cracks with the ART2-based RBF(Radial Basis Function) neural network. The proposed ART2-based RBF neural network applied ART2 to the learning between the input layer and the middle layer and the Delta learning method to the learning between the middle layer and the output layer. The experiments using real concrete crack images showed that the cracks in the concrete crack images were effectively extracted and the proposed ART2-based RBF neural network was effective in the recognition of the extracted cracks directions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Lee, B.Y., Kim, Y.Y., Kim, J.K.: Development of Image Processing for Concret Surface Cracks by Employing Enhanced Binarization and Shape Analysis Technique. Journal of the Korea Concrete Institute 17(3), 361–368 (2005)

    Article  Google Scholar 

  2. Lee, B.Y., Park, Y.D., Kim, J.K.: A Technique for Pattern Recognition of Concrete Surface Cracks. Journal of the Korea Concrete Institute 17(3), 369–374 (2005)

    Article  Google Scholar 

  3. Kim, Y.S., Haas, C.T.: An Algorithm for Automatic Crack Detection, Mapping and Representation. KSCE Journal of Civil Engineering 4(2), 103–111 (2000)

    Google Scholar 

  4. Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital Image Processing. Pearson Prentice Hall, London (2004)

    Google Scholar 

  5. Pitas, I.: Digital Image Processing Algorithms and Applications. John Wiley & Sons INC, Chichester (2000)

    Google Scholar 

  6. Panchapakesan, C., Ralph, D., Palaniswami, M.: Effects of Moving the Centers in an RBF Network. In: Proceedings of IJCNN, vol. 2, pp. 1256–1260 (1998)

    Google Scholar 

  7. Kim, K.B., Joo, Y.H., Cho, J.H.: An enhanced fuzzy neural network. In: Liew, K.-M., Shen, H., See, S., Cai, W. (eds.) PDCAT 2004. LNCS, vol. 3320, pp. 176–179. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  8. Pandya, A.S., Macy, R.B.: Neural Networks for Pattern Recognition using C++. IEEE Press and CRC Press (1995)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Silla University, Busan, 617-736, Korea

    Kwang-Baek Kim

  2. Department of Multimedia Engineering, Dongseo University, Busan, 617-716, Korea

    Hwang-Kyu Yang

  3. Department of Architectural Engineering, Silla University, Busan, 617-736, Korea

    Sang-Ho Ahn

Authors
  1. Kwang-Baek Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hwang-Kyu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sang-Ho Ahn
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina Gavrilova

  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  5. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  7. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea

    Hyunseung Choo

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kim, KB., Yang, HK., Ahn, SH. (2006). Recognition of Concrete Surface Cracks Using ART2-Based Radial Basis Function Neural Network. In: Gavrilova, M., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3982. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751595_31

Download citation

  • DOI: https://doi.org/10.1007/11751595_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34075-1

  • Online ISBN: 978-3-540-34076-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics