Iconic indexing by 2-D strings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Applications of spatial data structures: Computer graphics, image processing, and GIS
Applications of spatial data structures: Computer graphics, image processing, and GIS
Similarity retrieval of iconic image database
Pattern Recognition
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
Data structures and algorithms for nearest neighbor search in general metric spaces
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
Data Structures for Range Searching
ACM Computing Surveys (CSUR)
Searching Multimedia Databases by Content
Searching Multimedia Databases by Content
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Image indexing and similarity retrieval based on spatial relationship model
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Introduction to multimedia and mobile agents
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Spatial relations between objects are widely used in content-based image retrieval. This paper presents an algorithm for matching spatial relations using dynamic bintree (db-tree). A db-tree is balanced and has no coordinates. Its leaf nodes contain the images objects, and the internal nodes and the tree structure indicate the spatial relations among image objects. The time complexity of our matching algorithm is O(n lg m + n), where n and m are the number of objects in a query image and a database image. We have compared the db-tree data structure and the matching algorithm with other schemes, such as 2d-strings. For applications like "Campus Event" image retrieval, the theoretical analysis and experimental results show that the db-tree approach out-peiforms 2d-strings in several aspects.