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Robust Harris-Laplace Detector by Scale Multiplication

  • Fanhuai Shi
  • Xixia Huang
  • Ye Duan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Image Noise Scale Multiplication Corner Detection Weak Feature Harris Corner 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Fanhuai Shi
    • 1
    • 2
  • Xixia Huang
    • 3
  • Ye Duan
    • 1
  1. 1.Computer Science DepartmentUniversity of Missouri-ColumbiaUSA
  2. 2.Welding Engineering InstituteShanghai Jiao Tong UniversityChina
  3. 3.Marine Technology & Control Engineering Key LabShanghai Maritime UniversityChina

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