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Proceedings of the 2012 International Conference on Cybernetics and Informatics pp 285–291Cite as

An Approach for Image Retrieval Using SVM

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 163))

Abstract

In this paper, statistical learning method is used to attack the problems in content-based image retrieval. This paper presents a new, scaling and rotation invariant encoding scheme for shapes. We developed a common framework to deal with the problem of training with small samples. SVMs are used for the classifications of shapes encoded by the new method. This paper examines the performance of the proposed method by comparing it with that of multilayer perception based on real real-world image data. The experiment shows that the results of one-class SVMs outperform those of ANNs.

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Author information

Authors and Affiliations

  1. School of Computer and Information Engineering, Shanghai University of Electric Power, Shanghai, 200090, China

    Hui Liu

  2. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

    Ke Xu

Authors
  1. Hui Liu
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  2. Ke Xu
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Corresponding author

Correspondence to Hui Liu .

Editor information

Editors and Affiliations

  1. College of Elementary Education, Chongqing Normal University, Chongqing, People's Republic of China

    Shaobo Zhong

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Liu, H., Xu, K. (2014). An Approach for Image Retrieval Using SVM. In: Zhong, S. (eds) Proceedings of the 2012 International Conference on Cybernetics and Informatics. Lecture Notes in Electrical Engineering, vol 163. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3872-4_37

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  • DOI: https://doi.org/10.1007/978-1-4614-3872-4_37

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-3871-7

  • Online ISBN: 978-1-4614-3872-4

  • eBook Packages: EngineeringEngineering (R0)

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