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International Symposium on Visual Computing

ISVC 2009: Advances in Visual Computing pp 265–274Cite as

Robust Harris-Laplace Detector by Scale Multiplication

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5875))

Abstract

This paper proposes a robust Harris-Laplace detector by scale multiplication. The specific Harris corner measure functions at adjacent scales are multiplied as a product function to magnify the corner like structures, while suppress the image noise and weak features simultaneously. Unlike the contour-based multi-scale curvature product for image corner detection, we detect the corner like features directly in intensity image. Experiments on natural images demonstrate that the proposed method has good consistency of corner detection under different noise levels.

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Author information

Authors and Affiliations

  1. Computer Science Department, University of Missouri-Columbia, USA

    Fanhuai Shi & Ye Duan

  2. Welding Engineering Institute, Shanghai Jiao Tong University, China

    Fanhuai Shi

  3. Marine Technology & Control Engineering Key Lab, Shanghai Maritime University, China

    Xixia Huang

Authors
  1. Fanhuai Shi
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  2. Xixia Huang
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  3. Ye Duan
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, 338-8570, Saitama, Japan

    Yoshinori Kuno

  6. Institute for Infocomm Research, 21 Heng Mui Keng Terrace, P.O. Box, 119613, Singapore

    Junxian Wang

  7. Department of Computer Science & Information Engineering, Tamkang University, Tamsui, Taipei, Taiwan, R.O.C.

    Jun-Xuan Wang

  8. Microsoft Research, Redmond, WA, USA

    Junxian Wang

  9. Department of Informatics, Univ. of Zurich, Winterthurerstr. 190, P.O. Box, 8057, Zurich, Switzerland

    Renato Pajarola

  10. Lawrence Livermore National Laboratory, 94550, Livermore, CA, USA

    Peter Lindstrom

  11. University of Applied Sciences Bonn-Rhein-Sieg, 53754, Sankt Augustin, Germany

    André Hinkenjann

  12. Humana Inc., 40202, Louisville, KY, USA

    Miguel L. Encarnação

  13. SCI Institute & School of Computing, University of Utah, 84112, Salt Lake City, UT, USA

    Cláudio T. Silva

  14. Desert Research Institute, 89512, Reno, NV, USA

    Daniel Coming

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© 2009 Springer-Verlag Berlin Heidelberg

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Cite this paper

Shi, F., Huang, X., Duan, Y. (2009). Robust Harris-Laplace Detector by Scale Multiplication. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5875. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10331-5_25

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  • DOI: https://doi.org/10.1007/978-3-642-10331-5_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10330-8

  • Online ISBN: 978-3-642-10331-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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