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Shearlet-based detection of flame fronts

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Abstract

Identifying and characterizing flame fronts is the most common task in the computer-assisted analysis of data obtained from imaging techniques such as planar laser-induced fluorescence (PLIF), laser Rayleigh scattering (LRS), or particle imaging velocimetry (PIV). We present Complex Shearlet-Based Ridge and Edge Measure (CoShREM), a novel edge and ridge (line) detection algorithm based on complex-valued wavelet-like analyzing functions—so-called complex shearlets—displaying several traits useful for the extraction of flame fronts. In addition to providing a unified approach to the detection of edges and ridges, our method inherently yields estimates of local tangent orientations and local curvatures. To examine the applicability for high-frequency recordings of combustion processes, the algorithm is applied to mock images distorted with varying degrees of noise and real-world PLIF images of both OH and CH radicals. Furthermore, we compare the performance of the newly proposed complex shearlet-based measure to well-established edge and ridge detection techniques such as the Canny edge detector, another shearlet-based edge detector, and the phase congruency measure.

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Notes

  1. While the corresponding ground-truth is often created applying one of the edge detectors on the noiseless image, in this case, it was handmade by the authors to prevent favoring a particular method.

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Authors and Affiliations

  1. Computational Data Analysis, Fachbereich 3, Universität Bremen, Postfach 330440, 28334, Bremen, Germany

    Rafael Reisenhofer & Emily J. King

  2. Technische Thermodynamik, Fachbereich 4, Universität Bremen, Badgasteiner Str. 1, 28359, Bremen, Germany

    Johannes Kiefer

Authors
  1. Rafael Reisenhofer
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  2. Johannes Kiefer
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  3. Emily J. King
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Correspondence to Johannes Kiefer.

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Reisenhofer, R., Kiefer, J. & King, E.J. Shearlet-based detection of flame fronts. Exp Fluids 57, 41 (2016). https://doi.org/10.1007/s00348-016-2128-6

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