Harmonic Filters for Generic Feature Detection in 3D

  • Marco Reisert
  • Hans Burkhardt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5748)

Abstract

This paper proposes a concept for SE(3)-equivariant non-linear filters for multiple purposes, especially in the context of feature and object detection. The idea of the approach is to compute local descriptors as projections onto a local harmonic basis. These descriptors are mapped in a non-linear way onto new local harmonic representations, which then contribute to the filter output in a linear way. This approach may be interpreted as a kind of voting procedure in the spirit of the generalized Hough transform, where the local harmonic representations are interpreted as a voting function. On the other hand, the filter has similarities with classical low-level feature detectors (like corner/blob/line detectors), just extended to the generic feature/object detection problem. The proposed approach fills the gap between low-level feature detectors and high-level object detection systems based on the generalized Hough transform. We will apply the proposed filter to a feature detection task on confocal microscopical images of airborne pollen and compare the results to a 3D-extension of a popular GHT-based approach and to a classification per voxel solution.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Marco Reisert
    • 1
  • Hans Burkhardt
    • 2
    • 3
  1. 1.Dept. of Diagnostic Radiology, Medical PhysicsUniversity Medical CenterGermany
  2. 2.Computer Science DepartmentUniversity of FreiburgGermany
  3. 3.Centre for Biological Signaling Studies (bioss)University of FreiburgGermany

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