Iconic indexing by 2-D strings
IEEE Transactions on Pattern Analysis and Machine Intelligence
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
A New Way to Represent the Relative Position between Areal Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
IRM: integrated region matching for image retrieval
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Knowledge-Based Image Retrieval with Spatial and Temporal Constructs
IEEE Transactions on Knowledge and Data Engineering
Fast and robust recognition of orbit and sinus drawings using histograms of forces
Pattern Recognition Letters
Similarity Indexing with the SS-tree
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
The Use of Force Histograms for Affine-Invariant Relative Position Description
IEEE Transactions on Pattern Analysis and Machine Intelligence
WALRUS: A Similarity Retrieval Algorithm for Image Databases
IEEE Transactions on Knowledge and Data Engineering
Efficient update and retrieval of objects in a multiresolution geospatial database
SSDBM '03 Proceedings of the 15th International Conference on Scientific and Statistical Database Management
EBS k-d tree: an entropy balanced statistical k-d tree for image databases with ground-truth labels
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
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Geospatial information analysts are interested in spatial configurations of objects in satellite imagery and, more importantly, the ability to search a large-scale database of satellite images using spatial configurations as the query mechanism. In this paper we present a new method to model spatial relationships among sets of three or more objects in satellite images for scene indexing and retrieval by generating discrete spatial signatures. The proposed method is highly insensitive to scaling, rotation, and translation of the spatial configuration. Additionally, the method is efficient for use in real-time applications, such as online satellite image retrievals. Moreover, the number of objects in a spatial configuration has minimal effect on the efficiency of the method.