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- W3103770435 abstract "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-$alpha$ 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." @default.
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- W3103770435 date "2013-07-26" @default.
- W3103770435 modified "2023-09-27" @default.
- W3103770435 title "Optimization of Curvilinear Tracing Applied to Solar Physics and Biophysics" @default.
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- W3103770435 doi "https://doi.org/10.3390/e15083007" @default.
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