DocumentCode
3259012
Title
A Semi-Structured representation for Knowledge Discovering using Remote Sensing Images
Author
Lopez-Ornelas, Erick ; Sedes, Florence
Author_Institution
Univ. Autonoma Metropolitana-Unidad Cuajimalpa, Mexico
fYear
2006
fDate
Dec. 2006
Firstpage
24
Lastpage
28
Abstract
In this paper we describe the basic functionalities of a system dedicated to process high-resolution satellite images and to handle them through (semi-) structured descriptors. These descriptors enable to manage in a unified representation two families of features extracted from the objects identified by image segmentation: the attributes characterizing each object, and the attributes characterizing relationships between objects. Our aim is to focus on the complementary of two approaches, on one hand concerns the remote sensing and the image segmentation, and on the other hand concerns the knowledge discovery and the modeling
Keywords
data mining; feature extraction; image segmentation; remote sensing; feature extraction; high-resolution satellite images; image segmentation; knowledge discovery; remote sensing images; semistructured descriptors; semistructured representation; Availability; Data mining; Feature extraction; Image edge detection; Image segmentation; Morphology; Radiometry; Remote sensing; Satellite broadcasting; Spatial resolution;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location
Hong Kong
Print_ISBN
0-7695-2702-7
Type
conf
DOI
10.1109/ICDMW.2006.21
Filename
4063592
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