Details
| Original language | English |
|---|---|
| Title of host publication | Pattern Recognition - 24th DAGM Symposium, Proceedings |
| Editors | Luc Van Gool, Luc Van Gool, Luc Van Gool |
| Pages | 58-65 |
| Number of pages | 8 |
| Publication status | Published - 2002 |
| Event | 24th Symposium of the German Pattern Recognition Association, DAGM 2002 - Zurich, Switzerland Duration: 16 Sept 2002 → 18 Sept 2002 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 2449 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
Automatic interpretation of remote sensing data gathers more and more importance for surveillance tasks, reconnaissance and automatic generation and quality control of geographic maps. Methods and applications exist for structural analysis of image data as well as specialized segmentation algorithms for certain object classes. At the Institute of Communication Theory and Signal Processing focus is set on procedures that incorporate a priori knowledge into the interpretation process. Though many advanced image processing algorithms have been developed in the past, a disadvantage of earlier interpretation systems is the missing combination capability for the results of different - especially multisensor - image processing operators. The system GeoAIDA presented in this paper utilizes a semantic net to model a priori knowledge about the scene. The low-level, context dependent segmentation is accomplished by already existing, external image processing operators, which are integrated and controlled by GeoAIDA. Also the evaluation of the interpretation hypothesis is done by externaloperators, linked to the GeoAIDA system. As a result an interactive map with user selectable level-of-detail is generated.
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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Pattern Recognition - 24th DAGM Symposium, Proceedings. ed. / Luc Van Gool; Luc Van Gool; Luc Van Gool. 2002. p. 58-65 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2449 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A knowledge-based system for context dependent evaluation of remote sensing data
AU - Bückner, J.
AU - Pahl, M.
AU - Stahlhut, O.
AU - Liedtke, C. E.
PY - 2002
Y1 - 2002
N2 - Automatic interpretation of remote sensing data gathers more and more importance for surveillance tasks, reconnaissance and automatic generation and quality control of geographic maps. Methods and applications exist for structural analysis of image data as well as specialized segmentation algorithms for certain object classes. At the Institute of Communication Theory and Signal Processing focus is set on procedures that incorporate a priori knowledge into the interpretation process. Though many advanced image processing algorithms have been developed in the past, a disadvantage of earlier interpretation systems is the missing combination capability for the results of different - especially multisensor - image processing operators. The system GeoAIDA presented in this paper utilizes a semantic net to model a priori knowledge about the scene. The low-level, context dependent segmentation is accomplished by already existing, external image processing operators, which are integrated and controlled by GeoAIDA. Also the evaluation of the interpretation hypothesis is done by externaloperators, linked to the GeoAIDA system. As a result an interactive map with user selectable level-of-detail is generated.
AB - Automatic interpretation of remote sensing data gathers more and more importance for surveillance tasks, reconnaissance and automatic generation and quality control of geographic maps. Methods and applications exist for structural analysis of image data as well as specialized segmentation algorithms for certain object classes. At the Institute of Communication Theory and Signal Processing focus is set on procedures that incorporate a priori knowledge into the interpretation process. Though many advanced image processing algorithms have been developed in the past, a disadvantage of earlier interpretation systems is the missing combination capability for the results of different - especially multisensor - image processing operators. The system GeoAIDA presented in this paper utilizes a semantic net to model a priori knowledge about the scene. The low-level, context dependent segmentation is accomplished by already existing, external image processing operators, which are integrated and controlled by GeoAIDA. Also the evaluation of the interpretation hypothesis is done by externaloperators, linked to the GeoAIDA system. As a result an interactive map with user selectable level-of-detail is generated.
UR - http://www.scopus.com/inward/record.url?scp=75849146815&partnerID=8YFLogxK
U2 - 10.1007/3-540-45783-6_8
DO - 10.1007/3-540-45783-6_8
M3 - Conference contribution
AN - SCOPUS:75849146815
SN - 354044209X
SN - 9783540442097
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 58
EP - 65
BT - Pattern Recognition - 24th DAGM Symposium, Proceedings
A2 - Van Gool, Luc
A2 - Van Gool, Luc
A2 - Van Gool, Luc
T2 - 24th Symposium of the German Pattern Recognition Association, DAGM 2002
Y2 - 16 September 2002 through 18 September 2002
ER -