IEEE Transactions on Pattern Analysis and Machine Intelligence
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Training support vector machines with multiple equality constraints
ECML'05 Proceedings of the 16th European conference on Machine Learning
Morphological Component Analysis: An Adaptive Thresholding Strategy
IEEE Transactions on Image Processing
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In order to resolve the problem incurred by low efficient manual classification of tremendous aurora images, an automatic aurora images classification system for huge dataset application is proposed. First, static aurora images are decomposed into texture part and cartoon part with a method called Morphological Component Analysis (MCA). Then features extracted from texture part are classified by three classification methods: nearest neighbor (NN), Support Vector Machine (SVM) with RBF kernel and SVM with linear kernel. The experiment exhibited the classification accuracy improved by 10%, of which, the SVM with linear kernel is much faster and is therefore suitable for massive data processing.