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A Parabolic Detection Algorithm Based on Kernel Density Estimation

  • Conference paper
Emerging Intelligent Computing Technology and Applications (ICIC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5754))

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Abstract

The traditional Hough transform needs the edge detection in advance, so the effect of edge detection influences the final fitting result. This paper proposes a new method of detecting parabolas using the kernel density estimate based on the theory of Rozenn Dahyot, and extends this method into the eyelid detection in noisy images and other images including parabolas. In our paper, the edge detection is not necessary. On one hand, we not only consider the current points on the parabola, but also ones around the parabola. Experiments demonstrate that the proposed algorithm is robust and insensitive to the noise.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Hei Long Jiang University, Harbin, Hei Long Jiang Province, 150080, China

    Xiaomin Liu, Qi Song & Peihua Li

Authors
  1. Xiaomin Liu
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  2. Qi Song
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  3. Peihua Li
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, China

    De-Shuang Huang

  2. Graduate School of Electrical Engineering, University of Ulsan, Korea, San 29, Mugeo-Dong, Nam-Ku, 680 - 749, Ulsan, Korea

    Kang-Hyun Jo

  3. School of Electrical Engineering, University of Ulsan, Ulsan, South Korea

    Hong-Hee Lee

  4. School of Electrical Engineering, University of Ulsan, South Korea

    Hee-Jun Kang

  5. e.B.I.S. s.r.l. (electronic Business in Security), Spin-Off of Polytechnic of Bari, Str. Prov. per Casamassima Km., 3-70010, Valenzano, (BA), Italy

    Vitoantonio Bevilacqua

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© 2009 Springer-Verlag Berlin Heidelberg

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Liu, X., Song, Q., Li, P. (2009). A Parabolic Detection Algorithm Based on Kernel Density Estimation. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2009. Lecture Notes in Computer Science, vol 5754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04070-2_46

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  • DOI: https://doi.org/10.1007/978-3-642-04070-2_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04069-6

  • Online ISBN: 978-3-642-04070-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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