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International Symposium on Computational Intelligence and Intelligent Systems

ISICA 2015: Computational Intelligence and Intelligent Systems pp 275–283Cite as

SURF Feature Description of Color Image Based on Gaussian Model

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 575))

Abstract

To feature points description of color image, the fact that image color information has some effects on features of image is taken into consideration in this paper. And there is a novel method of SURF (speed up robust features) feature description of color image based on Gaussian color invariance model presented in this paper. During the stage of image feature description, the three kinds of color information in original color image are expressed by three components of Gaussian color invariance model respectively. Then, the matrix consisting of color invariants which are presented by Gaussian color invariance model represents original color image. Hereafter, the method of SURF feature description is used for describing the distribution of feature points. Finally, through our experiences, the correct matching ratio of feature point pairs of our method is higher than some typical algorithms represented in resent years when the image appears affine and blurring transformation.

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Acknowledgements

This work is supported by National Science Foundation of China (No. 61170161, No. 61300155, No. 61503219), Outstanding Young Scientists Foundations Grant of Shandong Province (No. BS2014DX016), Ph.D. Programs Foundation of Ludong University (No. LY2014033, LY2015033). This work is partially supported by NSFC Grants (61503219).

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Authors and Affiliations

  1. School of Information and Electrical Engineering, Ludong University, Yantai, 264025, China

    Wen Sun, Qian Shen & Chanjuan Liu

Authors
  1. Wen Sun
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  2. Qian Shen
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  3. Chanjuan Liu
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Corresponding author

Correspondence to Chanjuan Liu .

Editor information

Editors and Affiliations

  1. College of Mathematics and Informatics, The South China Agricultural University, Guangzhou, China

    Kangshun Li

  2. School of Computer Science, Guangzhou University, Guangzhou, China

    Jin Li

  3. School of Computer Science and Engineeri, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

  4. Dept. of Informatics, University of Salerno, Fisciano, Italy

    Aniello Castiglione

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© 2016 Springer Science+Business Media Singapore

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Sun, W., Shen, Q., Liu, C. (2016). SURF Feature Description of Color Image Based on Gaussian Model. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_28

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  • DOI: https://doi.org/10.1007/978-981-10-0356-1_28

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0355-4

  • Online ISBN: 978-981-10-0356-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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