Content-based image retrieval system using neural networks.

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

An effective image retrieval system is developed based on the use of neural networks (NNs). It takes advantages of association ability of multilayer NNs as matching engines which calculate similarities between a user's drawn sketch and the stored images. The NNs memorize pixel information of every size-reduced image (thumbnail) in the learning phase. In the retrieval phase, pixel information of a user's drawn rough sketch is inputted to the learned NNs and they estimate the candidates. Thus the system can retrieve candidates quickly and correctly by utilizing the parallelism and association ability of NNs. In addition, the system has learning capability: it can automatically extract features of a user's drawn sketch during the retrieval phase and can store them as additional information to improve the performance. The software for querying, including efficient graphical user interfaces, has been implemented and tested. The effectiveness of the proposed system has been investigated through various experimental tests.

Original languageEnglish
Pages (from-to)417-424
Number of pages8
JournalInternational Journal of Neural Systems
Volume10
Issue number5
Publication statusPublished - 2000 Oct

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Image retrieval
Neural networks
Pixels
Multilayer neural networks
Graphical user interfaces
Learning systems
Engines

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Content-based image retrieval system using neural networks. / Ikeda, T.; Hagiwara, Masafumi.

In: International Journal of Neural Systems, Vol. 10, No. 5, 10.2000, p. 417-424.

Research output: Contribution to journalArticle

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