Details
| Original language | English |
|---|---|
| Pages (from-to) | 311-317 |
| Number of pages | 7 |
| Journal | Information Fusion |
| Volume | 6 |
| Issue number | 4 |
| Early online date | 25 Sept 2004 |
| Publication status | Published - Dec 2005 |
Abstract
The task to update map databases regularly using images calls for automation. Within this process GIS and image data have to be combined. The different nature and content of these information sources prevent a direct comparison. In this paper an approach for the combination of GIS data and aerial images is proposed. We make use of a knowledge base, modelling the objects which are expected to be found. This leads to a refined image interpretation process and enables a revision of the GIS data. The focus is thereby on settlement and industrial areas which are detected automatically from images. The use of a semantic network allows the formulation of such complex objects expected in the image and supports decisions on a high level of abstraction. Reasoning is supported by using the existing GIS information for hypothesis generation. The decisions combine different clues which evolve during the image analysis process. The analysis generates a hierarchical scene description for the area of study and evaluates the correctness of the GIS data.
Keywords
- Decision level fusion, GIS, Knowledge based image interpretation, Quality control, Semantic net
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Computer Science(all)
- Signal Processing
- Computer Science(all)
- Information Systems
- Computer Science(all)
- Hardware and Architecture
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In: Information Fusion, Vol. 6, No. 4, 12.2005, p. 311-317.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - A framework for GIS and imagery data fusion in support of cartographic updating
AU - Weis, M.
AU - Müller, S.
AU - Liedtke, C. E.
AU - Pahl, M.
PY - 2005/12
Y1 - 2005/12
N2 - The task to update map databases regularly using images calls for automation. Within this process GIS and image data have to be combined. The different nature and content of these information sources prevent a direct comparison. In this paper an approach for the combination of GIS data and aerial images is proposed. We make use of a knowledge base, modelling the objects which are expected to be found. This leads to a refined image interpretation process and enables a revision of the GIS data. The focus is thereby on settlement and industrial areas which are detected automatically from images. The use of a semantic network allows the formulation of such complex objects expected in the image and supports decisions on a high level of abstraction. Reasoning is supported by using the existing GIS information for hypothesis generation. The decisions combine different clues which evolve during the image analysis process. The analysis generates a hierarchical scene description for the area of study and evaluates the correctness of the GIS data.
AB - The task to update map databases regularly using images calls for automation. Within this process GIS and image data have to be combined. The different nature and content of these information sources prevent a direct comparison. In this paper an approach for the combination of GIS data and aerial images is proposed. We make use of a knowledge base, modelling the objects which are expected to be found. This leads to a refined image interpretation process and enables a revision of the GIS data. The focus is thereby on settlement and industrial areas which are detected automatically from images. The use of a semantic network allows the formulation of such complex objects expected in the image and supports decisions on a high level of abstraction. Reasoning is supported by using the existing GIS information for hypothesis generation. The decisions combine different clues which evolve during the image analysis process. The analysis generates a hierarchical scene description for the area of study and evaluates the correctness of the GIS data.
KW - Decision level fusion
KW - GIS
KW - Knowledge based image interpretation
KW - Quality control
KW - Semantic net
UR - http://www.scopus.com/inward/record.url?scp=17444416073&partnerID=8YFLogxK
U2 - 10.1016/j.inffus.2004.08.001
DO - 10.1016/j.inffus.2004.08.001
M3 - Conference article
AN - SCOPUS:17444416073
VL - 6
SP - 311
EP - 317
JO - Information Fusion
JF - Information Fusion
SN - 1566-2535
IS - 4
ER -