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Combination of Keyword and Visual Feature based Image Retrieval System

http://hdl.handle.net/20.500.12678/0000004959
39dc34fa-7727-48a7-bd68-3cd6ee4e676f
6479a0a3-bb7d-4bd9-9814-f7a4a762d7e1
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psc2010paper psc2010paper (134).pdf (70 Kb)
Publication type
Article
Upload type
Publication
Title
Title Combination of Keyword and Visual Feature based Image Retrieval System
Language en
Publication date 2010-12-16
Authors
Kyaing, Htwe Htwe
Nge, Mi Mi
Description
Keyword-based image retrieval systems havebecome popular for many image databaseapplications. To improve the performance ofkeyword-based web image queries, combination ofkeyword and visual feature based image retrievalsystem is presented in this paper. Firstly, DOM(Document Object Model) trees are constructed fromcollected web pages. And several text blocks aresegmented based on text cohesion. Then, visualfeatures are extracted from color images in RGB(Red, Green and Blue) color space by using colorhistogram. When user query is entered, text blockswhich contain web images are taken as theassociated texts of corresponding images andTF*IDF values are used to index web images.Finally, keyword and visual features are combinedby using Gaussian Mixture Model to produce therelevance images.
Keywords
DOM tree, text cohesion, keyword, visual feature, Gaussian mixture model
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/858
Journal articles
Fifth Local Conference on Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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