| 英文摘要 | Located in the Western North Pacific and South China Sea basin, a region where the tropical cyclone (TC) activity is frequent and strongest, China is one of the countries that are seriously affected by TCs. In fact, the country suffers from TCs about 9-10 times per year on average, which causes serious property losses, life threats, and infrastructure damages. In order to reduce the disaster of a TC, it is important to precisely forecast its path, which needs to detect the existence of TC and locate its center in advance. It is a international problem. Among all the manners of monitoring TCs, satellites have the advantages of wide cover range, high quality, and multiple channels number compared with radars and planes. Hence, satellites have become the main tool in the detection and location of TCs. In this thesis, the efficient automatic detection and location of TCs using images from infrared satellites are investigated. The main contributions of the thesis are as follows. (1) In terms of detection TC, different TC detection algorithms are proposed according to detection purposes. The algorithm based on the classification of Histogram of Oriented Gradient (HOG) is applied for detecting the formative phase of TC. The false positive rate (FPR) and false negative rate (FNR) of the algorithm are 1.6% and 15.81%, respectively. Besides, a two-stage cascading algorithm is presented for detecting strong TC. The FPR and FNR of the two-stage algorithm are 3.1% and 4.86%, respectively. As a result, the TC region can be detected rapidly and precisely using the two-stage algorithm. (2) The idea of classification is proposed for the location of TC without history path information. Different location algorithms are used for different kinds of TCs. A classification method for TCs is presented based on the Term Frequency of Trend Line Codeword (TFTLC). First, trend lines are extracted from TC images. Then, the angle differences of the neighboring segments are encoded, and TC structures are clustered according to the codeword term frequency. Different location algorithms are designed for various structures, such as ellipse and spiral line, etc. Moreover, a method for locating TC is proposed based on ellipse fitting. The trend lines are fitted using ellipse model, and the ellipse centers are then clustered. The cluster with the most ellipses area selected for the computation of TC center, which is the mean of the mean of the centers of these ellipses. For the winding ... |
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