Details
| Original language | English |
|---|---|
| Title of host publication | 2009 Joint Urban Remote Sensing Event |
| Publication status | Published - 2009 |
| Event | 2009 Joint Urban Remote Sensing Event - Shanghai, China Duration: 20 May 2009 → 22 May 2009 |
Publication series
| Name | 2009 Joint Urban Remote Sensing Event |
|---|
Abstract
In this paper, a road extraction approach for suburban areas from high resolution CIR images is presented. The approach is region-based: the image is first segmented using the normalized cuts algorithm, then the initial segments are grouped to form segments, and road parts are extracted from these segments. Ideally roads in the image correspond to only one extracted road part, but they are often covered by several road parts with gaps between them. In order to combine these road parts, neighbouring road parts are connected to a road subgraph if there is evidence that they belong to the same road, such as similar direction and smooth continuation. This process allows several branches in the subgraph which is why another step follows to evaluate the subgraphs and divide them at gaps which show weak connections. The subgraph evaluation step is the focus of this paper. Linear programming is used for the subgraph evaluation after gap weights are determined. Two ways of determining gap weights are discussed, one using criteria which describe the properties of the road parts and their interrelations, and one using context objects (vehicles, trees, vegetation) in the gaps. The determination of the gap weights and the division of the road subgraphs is shown with an example.
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
- Computer Science(all)
- Computer Networks and Communications
- Environmental Science(all)
- Ecology
- Environmental Science(all)
- Nature and Landscape Conservation
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2009 Joint Urban Remote Sensing Event. 2009. 5137676 (2009 Joint Urban Remote Sensing Event).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Road extraction in suburban areas by region-based road subgraph extraction and evaluation
AU - Grote, Anne
AU - Heipke, Christian
AU - Rottensteiner, Franz
AU - Meyer, Hannes
PY - 2009
Y1 - 2009
N2 - In this paper, a road extraction approach for suburban areas from high resolution CIR images is presented. The approach is region-based: the image is first segmented using the normalized cuts algorithm, then the initial segments are grouped to form segments, and road parts are extracted from these segments. Ideally roads in the image correspond to only one extracted road part, but they are often covered by several road parts with gaps between them. In order to combine these road parts, neighbouring road parts are connected to a road subgraph if there is evidence that they belong to the same road, such as similar direction and smooth continuation. This process allows several branches in the subgraph which is why another step follows to evaluate the subgraphs and divide them at gaps which show weak connections. The subgraph evaluation step is the focus of this paper. Linear programming is used for the subgraph evaluation after gap weights are determined. Two ways of determining gap weights are discussed, one using criteria which describe the properties of the road parts and their interrelations, and one using context objects (vehicles, trees, vegetation) in the gaps. The determination of the gap weights and the division of the road subgraphs is shown with an example.
AB - In this paper, a road extraction approach for suburban areas from high resolution CIR images is presented. The approach is region-based: the image is first segmented using the normalized cuts algorithm, then the initial segments are grouped to form segments, and road parts are extracted from these segments. Ideally roads in the image correspond to only one extracted road part, but they are often covered by several road parts with gaps between them. In order to combine these road parts, neighbouring road parts are connected to a road subgraph if there is evidence that they belong to the same road, such as similar direction and smooth continuation. This process allows several branches in the subgraph which is why another step follows to evaluate the subgraphs and divide them at gaps which show weak connections. The subgraph evaluation step is the focus of this paper. Linear programming is used for the subgraph evaluation after gap weights are determined. Two ways of determining gap weights are discussed, one using criteria which describe the properties of the road parts and their interrelations, and one using context objects (vehicles, trees, vegetation) in the gaps. The determination of the gap weights and the division of the road subgraphs is shown with an example.
UR - http://www.scopus.com/inward/record.url?scp=70350151548&partnerID=8YFLogxK
U2 - 10.1109/URS.2009.5137676
DO - 10.1109/URS.2009.5137676
M3 - Conference contribution
AN - SCOPUS:70350151548
SN - 9781424434619
T3 - 2009 Joint Urban Remote Sensing Event
BT - 2009 Joint Urban Remote Sensing Event
T2 - 2009 Joint Urban Remote Sensing Event
Y2 - 20 May 2009 through 22 May 2009
ER -