The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
Overall Accuracy = (TP + TN) / Total number of pixels 
The Overall accuracy of our building detection system equals to 
95.1% which shows the percentage of correctly classified pixels. 
5. CONCLUSIONS AND FURTHER REASEARCH 
This paper presented an automatic building detection system by 
the use of LIDAR point cloud data provided in two individual 
files as first pulse and last pulse returns of laser pulse. Our 
system is comprised of five steps explained successively in 
section 3. In the resulting image, pixels are assigned either 
“Building” or “Non-building” labels. 
The results of the pixel-by-pixel comparison method used here 
proved that our building detection system has made some 
improvements in the detection task in comparison with some 
previous works. In addition to the Completeness and 
Correctness metrics, the evaluated 95.1% Overall accuracy of 
our system proves its efficiency and relatively high accuracy. 
We hope to make a clear comparison between our method and 
the existing ones in future works to claim the capabilities of our 
method. 
The study area contains a few flat-roofed, distanced buildings 
with some high-rise vegetation between them. So the accuracy 
of the system is not tested for any other scenes including 
complex scenes or dense urban areas. It is also recommended 
that the main version of Sohn filtering be used for more 
complex scenes and areas with significant topographic change 
effects. 
Different datasets including buildings with various roof types 
are recommended to be included for the assessment of the 
system, or any further corrections to the whole algorithm. 
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