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LiDAR data were read, remember the data were recorded 
disorderly. 
• Then it goes to calculate for edge detection and obtain 
edge and comer points by automatic judgments. 
• Isolating individual building objects. 
• Rebuilding the buildings by the linear features. 
• Evaluating by field survey. 
5. CONCLUSION 
This research is initial work carried out at the National Centre 
for Geocomputation Ireland for virtual campus building. Its aim 
is to set up effective and efficient algorithm for edge detection 
and make technique route to realize linear feature extraction 
from terrestrial LiDAR data. There still have much work to go 
further. The research put forward fractal dimension method for 
edge detection. It will be demonstrated with field terrestrial 
LiDAR data in the near future. 
REFERENCES 
Manohar M. and Paul C. 2006. Parallel algorithm for linear 
feature detection from airborne LiDAR data. Airborne 
Intelligence, Surveillance, Reconnaissance, Systems and 
Applications III, Proc. of SPIE Vol.6209, 620901, 2006. 
F. Samadzadegan. 2004. Object extraction and recognition from 
LiDAR data based on Fuzzy reasoning and information fusion 
techniques. www.isprs.org/istanbul2004 / comm7/papers 180.pdf 
Samuel P. K. and R. H. Cofer. 2005. Linear feature detection 
using multi-resolution wavelet filters. Photogrammetric 
Engineering & Remote Sensing. Vol.71, No.6.June 2005, 
pp689-697 
Suresh K. L., Darren M. F. and David P. H. 2007. Aerial 
LiDAR data classification using expectation-maximization. 
Vision Geometry XV, Proc. of SPIE-IS&T Electronic Imaging, 
SPIE Vol.6499, 64990L 
Arko L. and Alfred S. 2004. Texture-based landform 
segmentation of LiDAR imagery. International Journal of 
Applied Earth Observation and Geoinformation 6 (2005) 
261-270 
Paolo G., Bijan H. 2000. Digital Surface Models and Building 
Extraction: A Comparison of IFSAR and LIDAR Data. IEEE 
Transactions on Geoscience and Remote Sensing, Vol. 38, No. 
4, July 2000, pp1959-1968 
Zhang K. Q., Yan J. H. and Chen S. C.. 2006. Automatic 
Construction of Building Footprints From Airborne LIDAR 
Data. IEEE Transactions on Geoscience and Remote Sensing. 
Vol. 44, No. 9, September 2006 pp2523-2533 
George M. and Nikolaos K. 2007. Segmentation and 
object-based classification for the extraction of the building 
class from LIDAR DEMs. Computers & Geosciences 33 (2007) 
1076-1087 
Lindi J. Quackenbush. 2004. A Review of Techniques for 
Extracting Linear Features from Imagery. Photogrammetric 
Engineering & Remote Sensing, Vol.70,No.l2, December 2004, 
pp.1383-1392 
Qi Chen. 2007. Airborne Lidar Data Processing and Information 
Extraction. Photogrammetric Engineering & Remote Sensing. 
February 2007, pp. 109-112 
BC-CARMS. LiDAR - Overview of Technology, Applications, 
Market Features & Industry, 2006 
ZHENG Jianghua. YAN Lei, HE Kai and SUN Yongjun; The 
Fractal Method Study to Distinguish Road and Water from the 
IKONOS Image; Proceeding of IGARSS’05 
Yang Binli, Xiang Jianyong, Han Jiandong. A New Algorithm 
Based On Fractal Features For Fast Detection Of Man Made 
Objects In Nature Background [J], Laser & Infrared. 2003, 
33(5): 374-376. 
Li Qi, Fu Juncheng, Li Ziqin. Comparison of the edge detection 
algorithms for lidar image with speckle noise[J], Infrared and 
Laser Engineering, 2003, 32(3):240-243 
ACKNOWLEDGMENT 
The research is partly supported by a Special Postdoctoral 
Fellowship from National University of Ireland, Maynooth and 
the PhD Start-up Fund of Xinjiang University (ID: 070282)