Iconic indexing by 2-D strings
IEEE Transactions on Pattern Analysis and Machine Intelligence
A propositional modal logic of time intervals
Journal of the ACM (JACM)
Design and evaluation of algorithms for image retrieval by spatial similarity
ACM Transactions on Information Systems (TOIS)
Topological relations in the world of minimum bounding rectangles: a study with R-trees
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Information storage and retrieval
Information storage and retrieval
A spatial match representation scheme for indexing and querying in iconic image databases
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
Signature files: an access method for documents and its analytical performance evaluation
ACM Transactions on Information Systems (TOIS)
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Picture Similarity Retrieval Using the 2D Projection Interval Representation
IEEE Transactions on Knowledge and Data Engineering
Interval-Based Representation of Spatio-Temporal Concepts
CAiSE '97 Proceedings of the 9th International Conference on Advanced Information Systems Engineering
Mining spatial association rules in image databases
Information Sciences: an International Journal
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Because content-based image retrieval is essential to retrieve relevant multimedia documents, we represent images as a set of recognizable symbols, i.e., icon objects, and do indexing by regarding the icon object as a representative of a given document. When users request content-based image retrieval, we convert a query image into icon objects and retrieve relevant images in the database. In this paper, we propose a new spatial-match representation scheme, called SRR(Spatial-match Representation supporting Ranking) scheme, which combine directional operators with positional operators. Therefore, our SRR scheme can represent spatial relationships between icon objects precisely and can provide ranking for the retrieved images. In addition, we compare our scheme with the conventional 9DLT and SMR schemes in terms of retrieval effectiveness. Finally, we show from our experiment that our SRR scheme holds about 25% higher recall and about 10% higher precision, compared with the 9DLT and the SMR.