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Feature Based Image Retrieval Algorithm

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Advances in Computing and Communications (ACC 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 193))

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Abstract

The developments in the field of internet allow users in almost all the professional areas for exploiting the opportunities offered by the ability to access and manipulate remotely-stored images. The large multimedia database has to be processed within a small fraction of seconds for many of the real time applications. This demand of using the technique of content based image retrieval (CBIR) as a scheme for searching large database for image retrieval has addressed some of the issues that need to be solved for having an efficient system. The paper focuses on the issues of image retrieval and also suggests a method to get an accurate result by using a hybrid search methodology. The paper works in two phases- in the first phase it works with genetic algorithm to get a local optimal result and in the second phase, it works with neural network to get a global optimal result.

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References

  1. Yang, H., Zhou, X.: Research of Content based Image Retrieval Technology. In: Guangzhou, P.R. (ed.) Proceedings of the Third International Symposium on Electronic Commerce and Security Workshops (ISECS 2010), China, July 29-31, pp. 314–316 (2010)

    Google Scholar 

  2. Konstantinidis, K., Andreadis, I.: On the use of color histograms for content based image retrieval in various color spaces. In: ACM Proceeding ICCMSE 2003 Proceedings of the International Conference on Computational Methods in Sciences and Engineering ISBN:981-238-595-9

    Google Scholar 

  3. Deb, S., Zhang, Y.: An Overview of Content-based Image Retrieval Techniques. In: IEEE Proceedings of the 18th International Conference on Advanced Information Networking and Application, AINA 2004 (2004)

    Google Scholar 

  4. Fundamentals of content-based image retrieval, www.cse.iitd.ernet.in/~pkalra/siv864/Projects/ch01_Long_v40_proof.pdf

  5. Melanie, M.: An Introduction to Genetic Algorithms

    Google Scholar 

  6. Jose, T.J., Mythili: Neural Network and Genetic Algorithm based Hybrid model for content based mammogram Image Retrieval. Journal of Applied Sciences 9(19), 3531–3538 (2009) ISSN 1812-5654, Asian Network for Scientific Information

    Google Scholar 

  7. Content-based Image Retrieval - JISC, http://www.jisc.ac.uk/uploaded_documents/jtap-039.doc

  8. Eakins, J.: Content-Based Image Retrieval. Margaret Graham University of Northumbria at Newcastle. Report (October 39, 1999), http://www.cse.iitd.ernet.in/~pkalra/siv864/Projects/ch01_Long_v40_proof.pdf

  9. Varghese, T.A.: Performance Enhanced Optimization based Image Retrieval System. IJCA Special Issue on ”Evolutionary Computation for Optimization Techniques”, ECOT, 31–34 (2010)

    Google Scholar 

  10. Rezapour, O.M., Shui, L.T., Dehghani, A.A.: Review of Genetic Algorithm Model for Suspended Sediment Estimation. Australian Journal of Basic and Applied Sciences 4(8), 3354–3359 (2010) ISSN 1991-8178

    Google Scholar 

  11. Introduction to Genetic Algorithms and GAUL, http://gaul.sourceforge.net/intro.html

  12. Rajasekharan, S., Vijayalakshmi Pai, G.A.: Neural Networks, Fuzzy Logic, and Genetic Algorithm Synthesis and applications, Eastern Economy Edition

    Google Scholar 

  13. da Silva, S.F., Batista, M.A., Barcelos, C.A.Z.: Adaptive Image Retrieval through the use of a Genetic Algorithm. In: 19th IEEE International Conference on Tools with Artificial Intelligence, pp. 557–564 (2007)

    Google Scholar 

  14. Bio-inspired Computing, http://en.wikipedia.org/wiki/Bio-inspired_computing

  15. Bryden, J.: Biologically Inspired Computing: The Neural Network

    Google Scholar 

  16. Otair, M.A., Salameh, W.A.: Speeding Up Back-Propagation Neural Networks. In: Proceedings of the 2005 Informing Science and IT Education Joint Conference, Flagstaff, Arizona, USA, June 16-19 (2005)

    Google Scholar 

  17. Least mean square algorithm, http://etd.lib.fsu.edu/theses/available/etd-04092004-143712/unrestricted/Ch_6lms.pdf

  18. Karaboga1, N., Cetinkaya, B.: Design of Minimum Phase Digital IIR Filters by Using Genetic Algorithm. In: Proceedings of the 6th Nordic Signal Processing Symposium - NORSIG 2004, Espoo, Finland, June 9-11 (2004)

    Google Scholar 

  19. Sharpe, P.K., Greenwood, A., Chalmers, A.G.: Genetic Algorithms for Generating Minimum Path Configurations.

    Google Scholar 

  20. Ignatova, T., Heuer, A.: Model-Driven Development of Content-Based Image Retrieval Systems. Journal of Digital Information Management

    Google Scholar 

  21. Kerminen, P., Gabbouj, M.: Prototyping Color-based Image Retrieval with MATLAB

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Rajagiri School of Engineering and Technology, Cochin, India

    P. U. Nimi & C. Tripti

Authors
  1. P. U. Nimi
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  2. C. Tripti
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Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs (MIR Labs), Auburn, 98071-2259, Washington, USA

    Ajith Abraham

  2. Departamento de Comunicaciones, Universidad Politcnica de Valencia, 46071, Valencia, Spain

    Jaime Lloret Mauri

  3. Avaya Labs Research, Basking Ridge, NJ, USA

    John F. Buford

  4. University of Massachusetts, 100 Morrissey Blvd., 02125-3393, Boston, MA, USA

    Junichi Suzuki

  5. Rajagiri School of Engineering and Technology, Rajagiri Valley Kakkanad, 682 039, Kochi, India

    Sabu M. Thampi

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© 2011 Springer-Verlag Berlin Heidelberg

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Nimi, P.U., Tripti, C. (2011). Feature Based Image Retrieval Algorithm. In: Abraham, A., Mauri, J.L., Buford, J.F., Suzuki, J., Thampi, S.M. (eds) Advances in Computing and Communications. ACC 2011. Communications in Computer and Information Science, vol 193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22726-4_6

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  • DOI: https://doi.org/10.1007/978-3-642-22726-4_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22725-7

  • Online ISBN: 978-3-642-22726-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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