作者: F. Y. Shih , H. Wang , Gang Fu
DOI:
关键词: Kalman filter 、 Feature vector 、 Detection rate 、 Constant false alarm rate 、 Artificial intelligence 、 Pattern recognition 、 Support vector machine 、 Physics 、 Doppler effect 、 Harmonic filtering
摘要: In this paper, we present a novel method to detect Emerging Flux Regions (EFRs) in consecutive Michelson Doppler Imager (MDI) magnetograms. To our knowledge, is the first developed technique for automatically detecting EFRs. The includes several steps. First, projection distortion on MDI magnetograms corrected. Second, bipolar regions are extracted by applying multi-scale circular harmonic filters. Third, traced frames Kalman filter as candidate Fourth, properties, such positive and negative magnetic fluxes distance between two polarities, measured each frame. Finally, feature vector constructed region using Support Vector Machine (SVM) classifier applied distinguish EFRs from other regions. Experimental results show that detection rate of 96.4% nonEFRs 98.0%, false alarm 25.7%, based all available 2001 2002. Index Terms – flux region, Imager, filter, solar features