[[abstract]]Based on the S-tree, the modified S-tree is a newly proposed spatial data structure for representing digital binary images, which can support fast search and query in pictorial database. In this paper, we first present a new spatial data structure called the compact S-tree to represent binary images, which uses less memory when compared to the modified S-tree. We then present a fast search algorithm on the compact S-tree. Further, the application to neighbor finding is also investigated. Experimental results show that the proposed search algorithm is faster than the previous known results on the S-tree and the modified S-tree.
In this paper, the problem of indexing symbolic images based on spatial similarity is addressed. A m...
R-tree data structures are widely used in spatial databases to store, manage and manipulate spatial ...
In view of the low execution efficiency and poor practicability of the existing neighbor-finding met...
It is shown how a highly compact representation of binary trees can be used as the basis of two acce...
Abstra t | In this paper we propose and analyze a new spatial a ess method, namely the S tree, for ...
A simplified k nearest neighbour (knn) search for the R-tree family is proposed in this paper. This ...
Abstract: Nearest neighbor problem has special considerations among database researchers. In many ca...
Summarization: The state-of-the-art approach for speeding-up the time responses in databases is usin...
Image similarity search is a fundamental problem in computer vision. Efficient similarity search acr...
In this paper, we present a fast and versatile algorithm which can rapidly perform a variety of near...
[[abstract]]The problem of k-nearest neighbors (kNN) is to find the nearest k neighbors for a query ...
This paper develops the multidimensional binary search tree (or k-d tree, where k is the dimensional...
Data structures such as k-D trees and hierarchical k-means trees perform very well in approximate k ...
Large image and spatial databases are becoming more important in applications such as image archives...
A fundamental activity common to many image processing, pattern classification, and clustering algo...
In this paper, the problem of indexing symbolic images based on spatial similarity is addressed. A m...
R-tree data structures are widely used in spatial databases to store, manage and manipulate spatial ...
In view of the low execution efficiency and poor practicability of the existing neighbor-finding met...
It is shown how a highly compact representation of binary trees can be used as the basis of two acce...
Abstra t | In this paper we propose and analyze a new spatial a ess method, namely the S tree, for ...
A simplified k nearest neighbour (knn) search for the R-tree family is proposed in this paper. This ...
Abstract: Nearest neighbor problem has special considerations among database researchers. In many ca...
Summarization: The state-of-the-art approach for speeding-up the time responses in databases is usin...
Image similarity search is a fundamental problem in computer vision. Efficient similarity search acr...
In this paper, we present a fast and versatile algorithm which can rapidly perform a variety of near...
[[abstract]]The problem of k-nearest neighbors (kNN) is to find the nearest k neighbors for a query ...
This paper develops the multidimensional binary search tree (or k-d tree, where k is the dimensional...
Data structures such as k-D trees and hierarchical k-means trees perform very well in approximate k ...
Large image and spatial databases are becoming more important in applications such as image archives...
A fundamental activity common to many image processing, pattern classification, and clustering algo...
In this paper, the problem of indexing symbolic images based on spatial similarity is addressed. A m...
R-tree data structures are widely used in spatial databases to store, manage and manipulate spatial ...
In view of the low execution efficiency and poor practicability of the existing neighbor-finding met...