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Pattern Spectrum and Multiscale Shape Representation
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
Building efficient and flexible feature-based indices
Information Systems
A retrieval technique for similar shapes
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
International Journal of Computer Vision
Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
Fast multiresolution image querying
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
The SR-tree: an index structure for high-dimensional nearest neighbor queries
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Combining supervised learning with color correlograms for content-based image retrieval
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
The Grid File: An Adaptable, Symmetric Multikey File Structure
ACM Transactions on Database Systems (TODS)
MOSAIC: a fast multi-feature image retrieval system
Data & Knowledge Engineering
Indexing Techniques for Advanced Database Systems
Indexing Techniques for Advanced Database Systems
The K-D-B-tree: a search structure for large multidimensional dynamic indexes
SIGMOD '81 Proceedings of the 1981 ACM SIGMOD international conference on Management of data
An Evaluation of Color-Spatial Retrieval Techniques for Large Image Databases
Multimedia Tools and Applications
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The TV-tree: an index structure for high-dimensional data
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
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Feature-Based Retrieval of Similar Shapes
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The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Fast Nearest Neighbor Search in Medical Image Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Fast image retrieval using color-spatial information
The VLDB Journal — The International Journal on Very Large Data Bases
An Empirical Study of Color-Spatial Retrieval Techniques for Large Image Databases
ICMCS '98 Proceedings of the IEEE International Conference on Multimedia Computing and Systems
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Finding similar images quicky using object shapes
Proceedings of the tenth international conference on Information and knowledge management
An Information-Driven Framework for Image Mining
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
A new descriptor for shape recognition and retrieval
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
A robust shape retrieval method based on hough-radii
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
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In this paper, we address the following problem: given a large collection of shapes and a query shape, retrieve all shapes (from the shape database) that are similar to the query shape. A generalized centroid-radii model is used to model all forms of shapes — convex shapes, concave shapes and shapes with “holes”. Under the model, a shape is represented by a set of vectors, each obtained from the radii emanating from the centroid of a virtual concentric ring.The model can also facilitate multi-resolution and similarity retrievals. Furthermore, using the model, the shape of an object can be transformed into a point in a high dimensional data space. To speed up the retrieval of similar shapes, we also propose a multi-level R-tree index, called the Nested R-trees (NR-trees). Unlike traditional high-dimensional index structures that index a high-dimensional point as it is (with its full dimension), the NR-trees splits the dimensionality of the point into a set of lower dimensions that are indexed by levels of the NR-trees. We also proposed a quick filtering mechanism to further prune the search space.We implemented a shape retrieval system that employs the generalized centroid-radii model and the NR-trees with the filtering mechanism. Our experimental study shows the effectiveness of the proposed shape model, and the efficiency of the NR-trees. The results also show that the filtering mechanism can significantly reduce the retrieval time.