The Monogenic Curvature Scale-Space

  • Di Zang
  • Gerald Sommer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4040)


In this paper, we address the topic of monogenic curvature scale-space. Combining methods of tensor algebra, monogenic signal and quadrature filter, the monogenic curvature signal, as a novel model for intrinsically two-dimensional (i2D) structures, is derived in an algebraically extended framework. It is unified with a scale concept by employing damped spherical harmonics as basis functions. This results in a monogenic curvature scale-space. Local amplitude, phase and orientation, as independent local features, are extracted. In contrast to the Gaussian curvature scale-space, our approach has the advantage of simultaneous estimation of local phase and orientation. The main contribution is the rotationally invariant phase estimation in the scale-space, which delivers access to various phase-based applications in computer vision.


Spherical Harmonic Curvature Tensor Local Phase Geometric Algebra Main Orientation 
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 2006

Authors and Affiliations

  • Di Zang
    • 1
  • Gerald Sommer
    • 1
  1. 1.Cognitive Systems Group, Institute of Computer Science and Applied MathematicsChristian Albrechts University of KielKielGermany

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