An automated technique to segment solar coronal loops from intensity images of the Sun's corona is introduced. It exploits physical characteristics of the solar magnetic field to enable robust extraction from noisy images. The technique is a constructive curve detection approach, constrained by collections of estimates of the magnetic field's orientation. Its effectiveness is evaluated through experiments on synthetic and real coronal images.
G. Allen Gary, Jong Kwan Lee, Timothy S. Newman