The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
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Figure 7. Original image of pavement cracks 
TCLING Thresholding Image 
Figure 8. Binary image (proposed algorithm) 
of pavement cracks 
3.2.4 Morphological Closing 
Figure 9, which is a segmented image of Figure 7, shows how 
some noise cluster occupies open space corresponding to the 
background. Noise removal at the threshold of 10 pixels was 
applied, followed by performing morphological closing with 
structural element of size 5, than producing another binary 
image. The resulting aspect is shown in the sample of Figure 
10, where it can be noticed that some of the noises have been 
removed and some holes being filled with object pixels. 
3.2.5 Thinning Algorithm 
The binary image with clusters was not useful enough and had 
to be further processed by thinning. After thinning, a generic 
source image had the appearance as shown in Figure 11. Crack 
length was determined using the thinning algorithm based on 
the central lines with one pixel wide. Then, the average width 
of crack was obtained by dividing the area and the length. 
These parameters were found to be very beneficial for cracking 
quantification. 
Figure 9. Image segmented of Figure 3 before closing 
and noise removal 
Figure 10. Image segmented of Figure 7 after closing 
and noise removal 
Figure 11. Image of Figure 6 after thinning