Earticle

초록

영어

Automatic building extraction is one of the most important issues in the fields of geoscience and remote sensing. In this letter, by introducing the idea of area morphology to the analysis of 3-D point clouds, a novel approach for automatic building extraction from airborne LiDAR data was proposed. At first, single scale area opening and area closing operator was used to produce normalized point clouds. With the normalized point clouds as input, multi-scale area morphology was employed to obtain connected regions, and then tree points were removed by PCA based local structural analyzing technique. Finally, building regions were extracted by analyzing geometry properties of the obtained connected regions without tree points. Experiments for different terrains were conducted. And the corresponding experimental results are very promising.

목차

Abstract
 1. Introduction
 2. Multi-scale 3D Area Morphological Filtering Based Building Extraction
  2.1. D Area Morphology for Airborne LiDAR Point Clouds:
  2.2. Area Morphological Filtering Based Building Extraction
 3. Experimental Results
  3.1. Test Data sets
  3.2. Experimental Results
  3.3. Accuracy Assessment and Discussion
 4. Conclusions
 Acknowledgement
 References

키워드

저자

• Cao Zhimin [ School of Electronic Science, North-East Petroleum University, Daqing, China ]
• Wu Yun [ School of Electronic Science, North-East Petroleum University, Daqing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605