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
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
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)
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)
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)
Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital Image Processing. Pearson Prentice Hall, London (2004)
Pitas, I.: Digital Image Processing Algorithms and Applications. John Wiley & Sons INC, Chichester (2000)
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)
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)
Pandya, A.S., Macy, R.B.: Neural Networks for Pattern Recognition using C++. IEEE Press and CRC Press (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights 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)