Automatic Classification of Ultraviolet Aurora Images Based on Texture and Shape Features

Author

Han, Shenmiao ; Wu, Zhensen ; Wu, Guangli ; Tan, Jun

Author_Institution

Sch. of Sci., Xidian Univ., Xi´´an, China

fYear

2011

fDate

12-15 Aug. 2011

Firstpage

527

Lastpage

532

Abstract

Aurora is the typical ionosphere track generated by the interaction of solar wind and magnetosphere, and its detection is significant to study of space weather activity. Space-borne ultraviolet detectors, especially far ultraviolet band image detecting device, provide abundant detecting data. Based on the special morphology of ultraviolet aurora images, the combination of texture and shape features is utilized to extract the features of ultraviolet aurora images, and then a support vector machine (SVM) is employed to classify the auroras. The experiment based on ultraviolet aurora image data obtained by the Polar satellite shows the feasibility and effectiveness of our feature representation method.

Keywords

aurora; feature extraction; geophysical image processing; image classification; image representation; image texture; magnetosphere; solar wind; support vector machines; ultraviolet detectors; SVM; automatic ultraviolet aurora image classification; feature extraction; feature representation method; ionosphere; magnetosphere; polar satellite; shape features; solar wind; space weather activity; space-borne ultraviolet detector; support vector machine; texture features; ultraviolet aurora image morphology; ultraviolet band image detecting device; Accuracy; Feature extraction; Morphology; Satellites; Shape; Support vector machines; Training; aurora; shape feature; support vector machine; texture feature; ultraviolet;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Graphics (ICIG), 2011 Sixth International Conference on

Conference_Location

Hefei, Anhui

Print_ISBN

978-1-4577-1560-0

Electronic_ISBN

978-0-7695-4541-7

Type

conf

DOI

10.1109/ICIG.2011.12

Filename

6005608