Multi-feature vague fusion model for image classification
一种图像分类的多特征vague融合模型

For traditional way of image classification, feature fusion scheme would decrease classificatory quality or result in other problems such as curse of dimensionality.This paper proposed a novel approach trying to integrate different features in image classification. Vague set for positive and negativeevidences was applied to analyze and optimize the decisions obtained by multi-classifiers. Through integrating two sides of multiple classification decisions, the classification was optimized and synthesized, thus the processing and the result would be both powerful and stable. Experimental results show that the performance of the classification is greatly improved.