Journal of applied mathematics & informatics

The Korean Society for Computational and Applied Mathematics (한국전산응용수학회)
권호 표지

A METHOD OF IMAGE DATA RETRIEVAL BASED ON SELF-ORGANIZING MAPS

  • Lee, Mal-Rey (School of Multimedia, Yosu National University) ;
  • Oh, Jong-Chul (Faculty of Mathematics, Informatics and Statistics, Kunsan National University)
  • Published : 2002.05.01

⟨ Previous Next ⟩

Abstract

Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps (SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

Keywords

References

  1. Visual Explorations in Finance with Self-organizing Maps(Japanese ed.) Guido Deboek;Teuvo Kohonen
  2. Self-Organizing Maps, Series in Information Sciences(second edtiion) v.30 Kohonen,T.
  3. Basis and Application of Neural Network Baba,N.;Kojima,F.;Ozawa,M.
  4. Technical Report A31, Helsinki University of Technology, Laboratory of Computer and Information science SOM-PAK : The Self-Organizing Map Program Package Kohonen,T.;Hynninen,J.;Laaksonen,J.
  5. IEEE Computer v.28 no.9 Content-based image Retrieval System Gudivada,V.N.(ed.);Raghavan,V.V.(ed.)
  6. IEEE Computer v.28 no.9 Query by Image and Video Content: The QBIC System Flickner,M.(et al.)
  7. J. Intell. Inform. Syst. v.3 Efficient and Effective Query by Image Content Faloutsos,C.(et al.)
  8. Report to the JISC Technology Applications Programme Content-based image retrieval Eakins,J.P.;Graham,M.E.
  9. J. Visual Communication and Image Representation(JVCIR) v.10 no.1 Image Retrieval: Current Techniques, Promising Directions, and Open Issues Rui,Y.;Huang,T.;Chang,S.F.
  10. Proceedings of the ACM SIGMOD Conference Nearest neighbor queries N.Roussopoulos;S.Kelley;F.Vincent
  11. IEEE Trans. on Circuits and Systems for Video Technology, Special Issue on Segmentation, Description, and Retrieval of Video Content v.8 no.5 Relevance Feedback: A Power Tool in Interactive Content-Based Image Retrieval Yong Rui;Thomas S. Huang;Michael Ortega;Sharad Mehrotra
  12. IEEE Trans. Acoust. ,Speech and Signal Proc. v.37 no.12 Multifrequency channel decompositions of images and wavelet models Mallat,S.G.
  13. SPIE Storage and Retrieval for Image and Video Databases The QBIC project: Query Image by content using color, texture and shape Niblack,W.(et al.)
  14. Proc. ACM Intl. Conf. on Multimedia VisualSEEK : A Fully Automated Content-Based Image Query System Smith,J.R.;Chang,S.F.
  15. SPIE Storage and Retrieval for Image and Video Databases Ⅱ Photobook: Tools for Content - Based Manipulation of Image Databases Pentland,A.;Picard,R.W.;Schlaroff,S.
  16. Proc. SIGGRAPH95 Fast multiresolution Image Querying Jacobs,C.E.;Finkelstein,A.;Salesin,D.H.
  17. Ph.D.Dissertation, Dept. of Electrical and Computer Engineering, University of California NETRA : A Toolbox for Navigating Large Image Databases W.Y.Ma
  18. Proc. ICANN'99 Application of Tree Structured Self-Organizing Maps in Content-Based Image Retieval Laaksonen,J.;Koskela,M.;Oja,E.
  19. Proc. the 1999 Intl. Symp. on Database Applications in Non-Traditional Environments(DANTE'99) Image Classification and Retrieval based on Wavelete-SOM Oh,K.S.;Kaneko,K.;Makinouchi,A.
  20. Proc. ECAI'94 Progress with the Tree-Structured Self-Organizing Map Koikkalainen,P.;Cohn,A.(ed.)