Scene image analysis by using the sandglass-type neural network with a factor analysis

Seiji Ito, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu, Sigeru Omatu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

It is difficult to obtain images only we want on the web. Because, enormous data exist in the web. A present detection system of images are keyword detection which is added the name of keyword for images. Therefore, it is very important and difficult to add the keyword for images. In this paper, keywords in the image are anahzed by using the factor analysis and the sandglass-type neural network (SNN) for image searching. As images preprocessing, objective images are segmented by the maximin-distance algorithm. Small regions are integrated into a near region. Thus, objective images are segmented into some region. After mis images preprocessing, keywords in images are analyzed by using factor analysis and a sandglass-type neural network (SNN) for image searching in this paper. Images data are compressed to a 2-dimensional space by using these two methods. This 2-dimensional data space is presented by a graph. Thus, keywords are analyzed in detail.

Original languageEnglish
Title of host publicationProceedings - 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Subtitle of host publicationComputational Intelligence in Robotics and Automation for the New Millennium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages994-997
Number of pages4
ISBN (Electronic)0780378660
DOIs
Publication statusPublished - 2003 Jan 1
Externally publishedYes
Event2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003 - Kobe, Japan
Duration: 2003 Jul 162003 Jul 20

Publication series

NameProceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA
Volume2

Other

Other2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003
CountryJapan
CityKobe
Period03/7/1603/7/20

Keywords

  • Factor analysis
  • Integrated small region
  • Maximin-distance algorithm
  • Median filtering
  • SNN

ASJC Scopus subject areas

  • Computational Mathematics

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  • Cite this

    Ito, S., Mitsukura, Y., Fukumi, M., Akamatsu, N., & Omatu, S. (2003). Scene image analysis by using the sandglass-type neural network with a factor analysis. In Proceedings - 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation: Computational Intelligence in Robotics and Automation for the New Millennium (pp. 994-997). [1222315] (Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIRA.2003.1222315