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Proceedings Paper

Typhoon center location algorithm based on fractal feature and gradient of infrared satellite cloud image
Author(s): Changjiang Zhang; Yuan Chen; Juan Lu
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Paper Abstract

An efficient algorithm for typhoon center location is proposed using fractal feature and gradient of infrared satellite cloud image. The centers are generally located in this region for a typhoon except the latter disappearing typhoon. The characteristics of dense cloud region are smoother texture and higher gray values than those of marginal clouds. So the window analysis method is used to select an appropriate cloud region. The window whose difference value between the sum of the gray-gradient co-occurrence matrix and fractal dimension is the biggest is chosen as the dense cloud region. The temperature gradient of the region, which is near typhoon center except typhoon eye, is small. Thus the gradient information is strengthened and is calculated by canny operator. Then we use a window to traverse the dense cloud region. If there is a closed curve, the region of curve is considered as the typhoon center region. Otherwise, the region in which there is the most texture intersection and the biggest density is considered as the typhoon center region. Finally, the geometric center of the center region is determined as the typhoon center location. The effectiveness is test by Chinese FY-2C stationary satellite cloud image. And the result is compared with the typhoon center location in the “tropical cyclone yearbook” which was compiled by Shanghai typhoon institute of China meteorological administration. Experimental results show that the high location accuracy can be obtained.

Paper Details

Date Published: 18 November 2014
PDF: 6 pages
Proc. SPIE 9299, International Symposium on Optoelectronic Technology and Application 2014: Optical Remote Sensing Technology and Applications, 92990F (18 November 2014); doi: 10.1117/12.2070666
Show Author Affiliations
Changjiang Zhang, Zhejiang Normal Univ. (China)
Yuan Chen, Zhejiang Normal Univ. (China)
Juan Lu, Zhejiang Normal Univ. (China)


Published in SPIE Proceedings Vol. 9299:
International Symposium on Optoelectronic Technology and Application 2014: Optical Remote Sensing Technology and Applications
Anatoli G. Borovoi; Dong Liu, Editor(s)

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