The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B5. Beijing 2008 
571 
Figure 8 Point hue (left), saturation (middle) and values (right) 
of wall 1. The masonry wall is made of tightly packed granite 
stones, hence the hue and saturation components have almost 
uniform shading through out, except for two of the stones. As 
expected the value component (representing the distribution of 
light on the wall) contains more information. 
Point and edge attributes were computed as in wall 1. The 
segmentation of the wall using the edge length and value is 
shown in Figure 9. 
Using edge length Using value 
Figure 9 Segmentation using edge length and value as edge 
strength criteria 
The two results are fairly similar. The most notable aspect of 
the result is that there is a lot of under segmentation within and 
on the edge of the bricks. It is suspected that these are caused 
by depressions/ protrusions on the surface of the bricks that 
cause discontinuities or cast shadows. This however needs to be 
further tested. Wall 2 shows the difficulty of segmenting tightly 
packed masonry walls. Nonetheless, while the segmentation is 
not good enough for a brick reconstruction, a visual comparison 
with the value image in Figure 8 and the segmentation result in 
figure 9 suggests that it is good enough for the purposes of 
detection. 
5.3 Discussion 
From tests carried out, the proposed general algorithm works if 
the mortar channel is deep enough to cause a discontinuity 
between the surface of the brick and the mortar and the scan is 
dense enough to capture the mortar between bricks (at least 
three points). Variable resolutions in the scan present the 
greatest challenge as they make the selection of a segmentation 
threshold difficult. Because of this it is best to detect bricks in 
single scans, to avoid the dense overlaps that are caused by the 
overlapping of two or more scans. 
Experience from several tests indicates that the problems 
attendant with every wall is different. Lighting conditions will 
vary, the material of both mortar and brick vary, the texture of 
the mortar and brick are not the same between walls. 
Furthermore the resolution of scans will also vary. Thus, a 
semi-automatic detection approach may be better than an 
automatic one. 
6. CONCLUSIONS 
Laser scanning for the documentation of walls is done primarily 
for the purposes of generating façade drawings, assessing 
structural damage and quality control during and after 
construction. However, detecting individual bricks should allow 
for greater enhancement and intelligence in these activities. For 
example, if the bricks in a wall are of a uniform size then 
detected misshapen bricks will hint at defects (such as cracks) 
in a wall. Furthermore, the deformation analysis of a wall can 
be done based on a brick by brick comparison as opposed to 
current techniques that use targets or surface matching. 
A semi-automatic algorithm and tool was developed and 
experiences during its development showed that the bricks in a 
wall can be detect fairly quickly and with a high level of 
accuracy. The development of the proposed algorithm is still in 
its early stages. Greater testing of suitable point and edge 
attributes need to be done. For example a shortcoming of the 
algorithm is that it does not use the normal at a point. Using the 
normal at a point in the computation of edge attributes will 
enhance the detection of discontinuities between bricks and 
mortar. As is, the algorithm is still naïve. More testing is 
required to improve the algorithm. But the results obtained thus 
far are encouraging. 
Segmenting embedded walls is complicated because the walls 
at different depths will contain points at different resolutions. 
To overcome the problem of segmenting embedded walls an 
optimum threshold selection technique has been proposed. The 
technique has the potential for wider application in segmenting 
other types of point clouds. 
ACKNOWLEDGEMENTS 
The author wishes to thank Prof. Heinz Ruther for providing the 
laser scanner data used in the tests. 
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