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A New Clustering Algorithm for Noisy Image Retrieval

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Intelligent Control and Innovative Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 110))

Abstract

The paper concerns an open problem in the area of content based image retrieval (CBIR) and presents an original method for noisy image data sets by applying an artificial immune system model. In this regard, appropriate feature extraction methods in addition to a beneficial similarity criterion contribute to retrieving images from a noisy data set precisely. The results show some improvement and resistance in the noise tolerance of content based image retrieval in a database of various images.

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Author information

Authors and Affiliations

  1. School of Computer Engineering, Iran University of Science & Technology, Tehran, Iran

    Morteza Analoui

  2. University of Science and Technology (IUST), Narmak, Tehran, Iran

    Morteza Analoui & Maedeh Beheshti

  3. University of Science and Technology (IUST), Tehran, Iran

    Maedeh Beheshti

Authors
  1. Morteza Analoui
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  2. Maedeh Beheshti
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Corresponding author

Correspondence to Maedeh Beheshti .

Editor information

Editors and Affiliations

  1. International Association of Engineers, Hung To Road, Unit 1, 1/F, 37-39, Hong Kong, China

    Sio Iong Ao

  2. Computer Science, Tijuana Institute of Technology, Chula Vista, 91909, California, USA

    Oscar Castillo

  3. , Faculty of Information Sciences & Eng., University of Canberra, Canberra, 2601, Aust Capital Terr, Australia

    Xu Huang

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Analoui, M., Beheshti, M. (2012). A New Clustering Algorithm for Noisy Image Retrieval. In: Ao, S., Castillo, O., Huang, X. (eds) Intelligent Control and Innovative Computing. Lecture Notes in Electrical Engineering, vol 110. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1695-1_22

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  • DOI: https://doi.org/10.1007/978-1-4614-1695-1_22

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-1694-4

  • Online ISBN: 978-1-4614-1695-1

  • eBook Packages: EngineeringEngineering (R0)

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