The design and analysis of spatial data structures
The design and analysis of spatial data structures
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
Linear clustering of objects with multiple attributes
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
CIKM '93 Proceedings of the second international conference on Information and knowledge management
Metadata for integrating speech documents in a text retrieval system
ACM SIGMOD Record
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Similarity Searching in Medical Image Databases
IEEE Transactions on Knowledge and Data Engineering
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
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In this paper, a Hierarchical Entropy based Representation for texture indexing HERTI is presented. The hypothesis is that any texture can be efficaciously represented by means of a 1-D signal obtained by a characteristic curve covering a square (uniform under a given criterion and a given segmentation) region. Starting from such a signal, HER can be then efficaciously applied, taking into account of its generality, for image retrieval by content. Moreover, a Spatial Access Method (SAM), i.e. k-d-Tree, has been utilized in order to improve the search performances. The results obtained on some databases show that HERTI achieves very good performances with few false alarms and dismissals.