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International Conference Image Analysis and Recognition

ICIAR 2010: Image Analysis and Recognition pp 263–273Cite as

Improving Accuracy of Optical Flow of Heeger’s Original Method on Biomedical Images

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6111))

Abstract

The paper is focused on the computation of optical flow from time-lapse 2D images acquired from fluorescence optical microscope. The Heeger’s traditional established method based on spatio-temporal filtering is adopted and modified in order to solve issues that arose from this sort of image data. In particular, a scheme for effective and fast computations of complex Gabor convolutions is used. The filter tuning is changed to better support the detection of movement. The least squares fitting of the original method is also revised. A parametric study was conducted to assess optimal parameters. With optimal parameters, the proposed method showed lower average angular errors than the original. C++ implementation is available on the author’s web pages.

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Author information

Authors and Affiliations

  1. Centre for Biomedical Image Analysis, Masaryk University, Brno, 602 00, Czech Republic

    Vladimír Ulman

Authors
  1. Vladimír Ulman
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Editor information

Editors and Affiliations

  1. Faculty of Engineering, Institute of Biomedical Engineering, Rua Dr. Roberto Frias, University of Porto, 4200-465, Porto, Portugal

    Aurélio Campilho

  2. Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, Ontario, Canada

    Mohamed Kamel

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Ulman, V. (2010). Improving Accuracy of Optical Flow of Heeger’s Original Method on Biomedical Images. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2010. Lecture Notes in Computer Science, vol 6111. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13772-3_27

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  • DOI: https://doi.org/10.1007/978-3-642-13772-3_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13771-6

  • Online ISBN: 978-3-642-13772-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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