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Optimization of Curvi-Linear Tracing Applied to Solar Physics and Biophysics View all abstracts by submitter

Markus J. Aschwanden   Submitted: 2013-07-18 12:23

We developed an automated pattern recognition code that is particularly well suited to extract one-dimensional curvi-linear features from two-dimensional digital images. A former version of this {sl Oriented Coronal CUrved Loop Tracing (OCCULT)} code was applied to spacecraft images of magnetic loops in the solar corona, recorded with the NASA spacecraft {sl Transition Region And Coronal Explorer (TRACE)} in extreme ultra-violet wavelengths. Here we apply an advanced version of this code ({sl OCCULT-2}) also to similar images from the {sl Solar Dynamics Observatory (SDO)}, to chromospheric H- α images obtained with the {sl Swedish Solar Telescope (SST)}, and to microscopy images of microtubule filaments in live cells in biophysics. We provide a full analytical description of the code, optimize the control parameters, and compare the automated tracing with visual/manual methods. The traced structures differ by up to 16 orders of magnitude in size, which demonstrates the universality of the tracing algorithm.

Authors: Markus J. Aschwanden, Bart De Pontieu, and Eugene A. Katrukha
Projects: None

Publication Status: Entropy, Special Issue on Advanced Signal Processing in Heliopspheric Physics, (in press)
Last Modified: 2013-07-18 18:46
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