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Combination of Keyword and Visual Feature based Image Retrieval System
http://hdl.handle.net/20.500.12678/0000004959
http://hdl.handle.net/20.500.12678/000000495939dc34fa-7727-48a7-bd68-3cd6ee4e676f
6479a0a3-bb7d-4bd9-9814-f7a4a762d7e1
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psc2010paper (134).pdf (70 Kb)
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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 |