Automatic crack detection on road imagery using anisotropic diffusion and region linkage

A novel strategy to automatically detect cracks in road pavement surface imagery, acquired by a laser imaging system, is proposed. It includes a new procedure to link fragments of crack regions based on a maximum a posteriori (map) classifier, which relies on a set of geometric characteristics of the segmented binary regions. The proposed system starts with an anisotropic diffusion filtering, to smooth image texture variations resulting from the type of sensor used. Then, a Gaussian function is used to model the histogram for pixels intensities below a certain value, which allows inferring the threshold level to be used for image segmentation. Next, less relevant binary regions are identified, being kept only if they are linked to relevant crack regions. Encouraging experimental crack detection results are presented based on real images captured along Canadian roads.

[1]  Suyash P. Awate,et al.  Unsupervised, information-theoretic, adaptive image filtering for image restoration , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Manuel Avila,et al.  Automatic detection and classification of defect on road pavement using anisotropy measure , 2009, 2009 17th European Signal Processing Conference.

[3]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  H. Tsuji,et al.  A nonlinear spatio-temporal diffusion and its application to prefiltering in MPEG-4 video coding , 2002, Proceedings. International Conference on Image Processing.

[5]  Du-Ming Tsai,et al.  Anisotropic diffusion with generalized diffusion coefficient function for defect detection in low-contrast surface images , 2010, Pattern Recognit..

[6]  Chun-Xia Zhao,et al.  Pavement Distress Detection Based on Nonsubsampled Contourlet Transform , 2008, 2008 International Conference on Computer Science and Software Engineering.

[7]  K. E. Tait,et al.  Image recovery using the anisotropic diffusion equation , 1996, IEEE Trans. Image Process..

[8]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[9]  Joachim Weickert,et al.  Anisotropic diffusion in image processing , 1996 .

[10]  Paulo Lobato Correia,et al.  Automatic road crack segmentation using entropy and image dynamic thresholding , 2009, 2009 17th European Signal Processing Conference.

[11]  Peggy Subirats,et al.  Introduction of a wavelet transform based on 2D matched filter in a Markov random field for fine structure extraction: application on road crack detection , 2009, Electronic Imaging.