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arXiv · 1511.03753

Shearlet-Based Detection of Flame Fronts

Rafael Reisenhofer·Johannes Kiefer·Emily J. King
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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 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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Rafael Reisenhofer, Johannes Kiefer, Emily J. King. 2016-02-03. Shearlet-Based Detection of Flame Fronts. https://doi.org/10.1007/s00348-016-2128-6

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