Volume 11, Issue 2 (3-2015)                   JSDP 2015, 11(2): 91-109 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

keyvanpour M. A Divisive Hierarchical Clustering-based Method for Indexing Image Information . JSDP. 2015; 11 (2) :91-109
URL: http://jsdp.rcisp.ac.ir/article-1-74-en.html
Abstract:   (5138 Views)
It is conventional to use multi-dimensional indexing structures to accelerate search operations in content-based image retrieval systems. Many efforts have been done in order to develop multi-dimensional indexing structures so far. In most practical applications of image retrieval, high-dimensional feature vectors are required, but current multi-dimensional indexing structures lose their efficiency with growth of dimensions. Increase in dimensions of data space leads to exponentially growth of the search space and increase of the number of nodes in multi-dimensional indexing structure, as well as increase in overlap between nodes in multi-dimensional indexing structures. These problems lead to increase in cost of search through indexing structure and therefore to reduction in efficiency of these structures in high-dimensional spaces. The main goal of this research is to propose a divisive hierarchical clustering-based multi-dimensional indexing structure in order to manage high-dimensional feature vectors extracted from images, which also prevents overlapping in its structure.Various tests and analyses of experimental results on high-dimensional datasets indicate the performance of our proposed method in comparison with others.
Full-Text [PDF 4949 kb]   (1247 Downloads)    
Type of Study: Research | Subject: Paper
Received: 2013/06/5 | Accepted: 2014/09/22 | Published: 2015/03/22 | ePublished: 2015/03/22

Add your comments about this article : Your username or Email:

© 2015 All Rights Reserved | Signal and Data Processing