Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2007 Urban Remote Sensing Joint Event |
| Untertitel | URS |
| Publikationsstatus | Veröffentlicht - 2007 |
| Veranstaltung | 2007 Urban Remote Sensing Joint Event, URS - Paris, Frankreich Dauer: 11 Apr. 2007 → 13 Apr. 2007 |
Abstract
This paper deals with the segmentation of images of suburban scenes with the Normalized Cut algorithm. The segmentation results are intended to be used for the extraction of roads in order to assess existing road data. The similarity matrix necessary for the Normalized Cuts algorithm is built up using similarity criteria that are suitable for the separation of road segments and non-road segments. These criteria are edges, colour, hue and road surface colour derived with the help of the database information which is thus used as prior information to facilitate the segmentation and extraction. Segmentation is the main topic of this paper, but some hints on future work regarding the selection of road segments based on road colour are given. The results show that the approach is suitable for the segmentation in order to extract roads in suburban scenes.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
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- BibTex
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2007 Urban Remote Sensing Joint Event: URS. 2007. 4234416.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Segmentation Based on Normalized Cuts for the Detection of Suburban Roads in Aerial Imagery
AU - Grote, Anne
AU - Butenuth, Matthias
AU - Gerke, Markus
AU - Heipke, Christian
N1 - Funding Information: This project is funded by the DFG (German Research Foundation). The calculations are made with a C++ program adapted from a MATLAB program written by Timothée Cour, Stella Yu and Jianbo Shi.
PY - 2007
Y1 - 2007
N2 - This paper deals with the segmentation of images of suburban scenes with the Normalized Cut algorithm. The segmentation results are intended to be used for the extraction of roads in order to assess existing road data. The similarity matrix necessary for the Normalized Cuts algorithm is built up using similarity criteria that are suitable for the separation of road segments and non-road segments. These criteria are edges, colour, hue and road surface colour derived with the help of the database information which is thus used as prior information to facilitate the segmentation and extraction. Segmentation is the main topic of this paper, but some hints on future work regarding the selection of road segments based on road colour are given. The results show that the approach is suitable for the segmentation in order to extract roads in suburban scenes.
AB - This paper deals with the segmentation of images of suburban scenes with the Normalized Cut algorithm. The segmentation results are intended to be used for the extraction of roads in order to assess existing road data. The similarity matrix necessary for the Normalized Cuts algorithm is built up using similarity criteria that are suitable for the separation of road segments and non-road segments. These criteria are edges, colour, hue and road surface colour derived with the help of the database information which is thus used as prior information to facilitate the segmentation and extraction. Segmentation is the main topic of this paper, but some hints on future work regarding the selection of road segments based on road colour are given. The results show that the approach is suitable for the segmentation in order to extract roads in suburban scenes.
UR - http://www.scopus.com/inward/record.url?scp=34648827376&partnerID=8YFLogxK
U2 - 10.1109/URS.2007.371817
DO - 10.1109/URS.2007.371817
M3 - Conference contribution
AN - SCOPUS:34648827376
SN - 1424407125
SN - 1-4244-0711-7
BT - 2007 Urban Remote Sensing Joint Event
T2 - 2007 Urban Remote Sensing Joint Event, URS
Y2 - 11 April 2007 through 13 April 2007
ER -