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Modeling of Remote Sensing Image Content using Attributed Relational Graphs

Summary: Modeling of Remote Sensing Image Content
using Attributed Relational Graphs
Selim Aksoy
Department of Computer Engineering, Bilkent University, Ankara, 06800, Turkey
Abstract. Automatic content modeling and retrieval in remote sens-
ing image databases are important and challenging problems. Statis-
tical pattern recognition and computer vision algorithms concentrate
on feature-based analysis and representations in pixel or region levels
whereas syntactic and structural techniques focus on modeling symbolic
representations for interpreting scenes. We describe a hybrid hierarchical
approach for image content modeling and retrieval. First, scenes are de-
composed into regions using pixel-based classifiers and an iterative split-
and-merge algorithm. Next, spatial relationships of regions are computed
using boundary, distance and orientation information based on differ-
ent region representations. Finally, scenes are modeled using attributed
relational graphs that combine region class information and spatial ar-
rangements. We demonstrate the effectiveness of this approach in query
scenarios that cannot be expressed by traditional approaches but where
the proposed models can capture both feature and spatial characteris-


Source: Aksoy, Selim - Department of Computer Engineering, Bilkent University


Collections: Computer Technologies and Information Sciences