Image retrieval system using R-tree self-organizing map

被引：10

作者：

Subramanyam Rallabandi, V. P. ^{[1
]}

Sett, S. K. ^{[1
]}

机构：

[1] Univ Delhi, Delhi Coll Engn, Dept Appl Math, Delhi 110042, India

来源：

DATA & KNOWLEDGE ENGINEERING | 2007年 / 61卷 / 03期

关键词：

relevance feedback; R-tree SOM; fuzzy color histogram; Bayesian distance; Lie algebra; diffeomorpbisms;

D O I：

10.1016/j.datak.2006.06.016

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Most of the retrieval systems concentrate much on low-level features such as color, texture, shape, position, etc. The present system is mainly developed based on the visual descriptors of the image such as color, texture and shape descriptors. We have used unsupervised Kohonen's self-organizing maps (SOM) technique to train the images and our own indexing scheme with reference system based on R-tree SOM. We proposed an approach, fuzzy color histogram, for color retrieval and Lie descriptors for the retrieval of shapes. We have performed experiments and tested the proposed approach with our own image database constructed from Corel photo gallery. (C) 2006 Elsevier B.V. All rights reserved.

引用

页码：524 / 539

页数：16

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