• May 03, 2016 News! IJIET Vol. 5, No. 10 has been indexed by EI (Inspec).   [Click]
  • Jun 28, 2017 News!Vol. 7, No. 9 has been indexed by Crossref.
  • Jun 22, 2017 News!Vol. 7, No. 9 issue has been published online!   [Click]
General Information
    • ISSN: 2010-3689
    • Frequency: Bimonthly (2011-2014); Monthly (Since 2015)
    • DOI: 10.18178/IJIET
    • Editor-in-Chief: Prof. Dr. Steve Thatcher
    • Executive Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: EI (INSPEC, IET), Electronic Journals Library, Google Scholar, Crossref and ProQuest
    • E-mail: ijiet@ejournal.net
Editor-in-chief
Prof. Dr. Steve Thatcher
University of South Australia, Australia
It is my honor to be the editor-in-chief of IJIET. The journal publishes good papers which focous on the advanced researches in the field of information and education technology. Hopefully, IJIET will become a recognized journal among the scholars in the filed of information and education technology.
IJIET 2014 Vol.4(6): 487-490 ISSN: 2010-3689
DOI: 10.7763/IJIET.2014.V4.456

Combination of Keyword and Visual Features for Web Image Retrieval System

Nyein Myint Myint Aung
Abstract—This paper presents the implementation of web image retrieval system using keyword-based search and visual image features. In order to correctly correlate terms to a web image, the associated text of the web image is partitioned into text blocks according to the structure of the text with respect to the web images. Then, keywords are extracted and stored in image indexing database which will later be used in keyword based retrieval. When user enters keyword, result images are generated by image indexing and searching algorithms. Most of the web image search systems are based on only keyword based searches. But most of the result images in the keyword search are not relevant to the query. To reduce the influence of those irrelevant images, visual image features are used. Firstly, image features are extracted and then they are stored in the image indexing database. And then these features are used to cluster images for relevant and non-relevant. Combination of keyword search and visual feature extraction will result in producing more relevant images by removing non-relevant images. Extracting visual features can improve the system performance.

Index Terms—Image retrieval system, keyword-based search, visual image features.

Nyein Myint Myint Aung is with University of Technology, Yatanarpon Cyber City, Myanmar (e-mail: thae.thae.star@gmail.com).

[PDF]

Cite: Nyein Myint Myint Aung, "Combination of Keyword and Visual Features for Web Image Retrieval System," International Journal of Information and Education Technology vol. 4, no. 6, pp. 487-490, 2014.

Copyright © 2008-2017. International Journal of Information and Education Technology. All rights reserved.
E-mail: ijiet@ejournal.net