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Cited by 269

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Filament identification through mathematical morphology

Open access
Koch, Eric W., Rosolowsky, Erik W.·2015·Monthly Notices of the Royal Astronomical Society

Abstract

We present a new algorithm for detecting filamentary structure FilFinder. The algorithm uses the techniques of mathematical morphology for filament identification, presenting a complementary approach to current algorithms which use matched filtering or critical manifolds. Unlike other methods, FilFinder identifies filaments over a wide dynamic range in brightness. We apply the new algorithm to far-infrared imaging data of dust emission released by the Herschel Gould Belt Survey team. Our preliminary analysis characterizes both filaments and fainter striations. We find a typical filament width of 0.09 pc across the sample, but the brightness varies from cloud to cloud. Several regions show a bimodal filament brightness distribution, with the bright mode (filaments) being an order of magnitude brighter than the faint mode (striations). Using the Rolling Hough Transform, we characterize the orientations of the striations in the data, finding preferred directions that agree with magnetic field direction where data are available. There is a suggestive but noisy correlation between typical filament brightness and literature values of the star formation rates for clouds in the Gould Belt.

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Metadata

Authors
Koch, E. W., & Rosolowsky, E. W.
Venue
Monthly Notices of the Royal Astronomical Society
Published
2015-08-04
Volume
452
Issue
4
Pages
3435-3450
ISSN
  • 0035-8711 (ISSN-L)
  • 1365-2966
OpenAlex
W1916448108
Cited by
269
References
28
FWCI
7.14
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Filament identification through mathematical morphology. https://app.cochat.ai/papers/10.1093/mnras/stv1521
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Koch, E. W., & Rosolowsky, E. W. (2015). Filament identification through mathematical morphology. Monthly Notices of the Royal Astronomical Society. https://doi.org/10.1093/mnras/stv1521

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