Intelligent Image Database for Nature Managment Optimization
| dc.contributor.author | Kovalevskaya, Nelley M. | |
| dc.contributor.editor | Cremers, Armin B. | |
| dc.contributor.editor | Greve, Klaus | |
| dc.date.accessioned | 2019-09-16T09:31:36Z | |
| dc.date.available | 2019-09-16T09:31:36Z | |
| dc.date.issued | 2000 | |
| dc.description.abstract | Intelligent image databases have to facilitate analyses of space and aerial observations of the environment processes and phenomena for estimation the environment current state. Such image databases should efficiently combine the experts' image interpretations and the corresponding environment knowledge. The paper demonstrates a new application of computer vision to image databases the use of image texture for annotation, the description of content. The goal was to use a scheme that is able to automatically decide on the image features and based upon psychophysical studies of human perception nature and computer vision models in contrast to multiple cue-based schemes being still heuristic. The approach provides a learning algorithm for selecting the most representative features of the homogeneous and piecewise-homogeneous data. Highly specializes and context-dependent features are extracted automatically and spatial information is preserved. | de |
| dc.identifier.uri | http://enviroinfo.eu/sites/default/files/pdfs/vol102/0571.pdf | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/26633 | |
| dc.publisher | Metropolis | |
| dc.relation.ispartof | Umweltinformatik ’00 Umweltinformation für Planung, Politik und Öffentlichkeit | |
| dc.relation.ispartofseries | EnviroInfo | |
| dc.title | Intelligent Image Database for Nature Managment Optimization | de |
| dc.type | Text/Conference Paper | |
| gi.citation.publisherPlace | Marburg | |
| gi.conference.date | 2000 | |
| gi.conference.location | Bonn | |
| gi.conference.sessiontitle | Anwendungen in der Fernerkundung; Applications in Remote Sensing |