Automatic solar filament detection using image processing techniques

Document Type

Article

Publication Date

5-1-2005

Abstract

We present an automatic solar filament detection algorithm based on image enhancement, segmentation, pattern recognition, and mathematical morphology methods. This algorithm cannot only detect filaments, but can also identify spines, footpoints, and filament disappearances. It consists of five steps: (1) The stabilized inverse diffusion equation (SIDE) is used to enhance and sharpen filament contours. (2) A new method for automatic threshold selection is proposed to extract filaments from local background. (3) The support vector machine (SVM) is used to differentiate between sunspots and filaments. (4) Once a filament is identified, morphological thinning, pruning, and adaptive edge linking methods are used to determine the filament properties. (5) Finally, we propose a filament matching method to detect filament disappearances. We have successfully applied the algorithm to Hα full-disk images obtained at Big Bear Solar Observatory (BBSO). It has the potential to become the foundation of an automatic solar filament detection system, which will enhance our capabilities of forecasting and predicting geo-effective events and space weather. © Springer 2005.

Identifier

25844514231 (Scopus)

Publication Title

Solar Physics

External Full Text Location

https://doi.org/10.1007/s11207-005-5780-1

ISSN

00380938

First Page

119

Last Page

135

Issue

1-2

Volume

228

Grant

ATM 02-33931

Fund Ref

National Science Foundation

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