Name
Abstract | ||
|---|---|---|
The success of automatic building detection techniques lies in the effective separation of buildings from trees. This paper presents an improved automatic building detection technique that achieves more effective separation of buildings from trees. Firstly, it uses cues such as height to remove objects of low height such as bushes, and width to exclude trees with small horizontal coverage. The height threshold is also used to generate a ground mask where buildings are found to be more separable than in a so-called normalized DSM (digital surface model). Secondly, image entropy and colour information are jointly applied to remove easily distinguishable trees. Finally, an innovative rule-based procedure is employed using the edge orientation histogram from the imagery to eliminate false positive candidates. While tested on a number of scenes from four different test areas, the improved algorithm performed well even in complex scenes which are hilly and densely vegetated. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICMEW.2012.96 | ICME Workshops |
Keywords | Field | DocType |
height threshold,complex scenes,low height,different test area,complex scene,effective separation,improved automatic building detection,improved algorithm,automatic building detection technique,improved building detection technique,digital surface model,colour information,vegetation,building,automatic,orthoimage,histograms,image segmentation,knowledge based systems,lidar,detectors | Computer vision,Object detection,Histogram,Normalization (statistics),Pattern recognition,Computer science,Image processing,Image segmentation,Lidar,Artificial intelligence,Detector,Orthophoto | Conference |
ISSN | Citations | PageRank |
2330-7927 | 1 | 0.39 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad Awrangjeb | 1 | 155 | 17.09 |
| Chunsun Zhang | 2 | 26 | 4.37 |
| Clive Fraser | 3 | 134 | 15.09 |