Automatic classification of ultraviolet aurora images based on texture and shape features

Shenmiao Han, Zhensen Wu, Guangli Wu, Jun Tan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationProceedings - 6th International Conference on Image and Graphics, ICIG 2011
Pages527-532
Number of pages6
DOIs
StatePublished - 2011
Event6th International Conference on Image and Graphics, ICIG 2011 - Hefei, Anhui, China
Duration: Aug 12 2011Aug 15 2011

Publication series

NameProceedings - 6th International Conference on Image and Graphics, ICIG 2011

Other

Other6th International Conference on Image and Graphics, ICIG 2011
Country/TerritoryChina
CityHefei, Anhui
Period8/12/118/15/11

Keywords

  • Aurora
  • Shape feature
  • Support vector machine
  • Texture feature
  • Ultraviolet

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'Automatic classification of ultraviolet aurora images based on texture and shape features'. Together they form a unique fingerprint.

Cite this