TC center location is important for weather forecast and TC analysis. However the appearance of TC centers has
different shapes and sizes at different time. At different stages of TC lifetime, the difficulty of locating TC center is
different. In order to improve the automatism and precision, we present a TC center location scheme for eye TCs and
non-eye TCs. Fisher discriminant is used to segment TC so that we can get the binary image automatically and
effectively. Since the cloud wall near the non-eye TC center is homocentric circle, Chan-Vese model is used to get TC
contour. Experimental results on TCs show that our scheme can achieve an average error within 0.3 degrees in
longitude/latitude in comparison with the best tracks by CMA and RSMC.
Tropical Cyclone (TC) center locating is a crucial step in analyzing TCs. TCs can be divided into Eye TC and No-eye
TC. Different TCs have different characters. Before locating its center, TC should be detected from the whole satellite
cloud image. Both infrared (IR) images and visible (VIS) images are used to detect TC. Some pattern recognition and
image processing methods are applied in the paper. They are well used both in detecting TCs and getting the centers of
Eye TCs. Gray Model and Chan-Vese model play important roles in locating the No-eye TCs' centers. Gray Model is
used to predict the initial position of the next TC center. Since the cloud wall near the No-eye TC center is homocentric
circle, Chan-Vese model (C-V model) is used to get TC contour. Experiments on MAN-YI (in 2007) and WUTIP (in
2007) show that the average error is within 0.2 degrees compared with the best track data supported by China
Meteorological Administration.
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