A Multi-Feature Fusion Approach to Image Classification Based on Vague Set

With the development of computer and network technologies, there has been an explosion in the volume of multimedia database. In order to make use of this vast volume of data, efficient and effective techniques to classify multimedia information need to be developed. This paper proposes a novel fusion approach to image classification based on vague sets, in which vague sets for positive and negative evidences is applied to analyze and optimize the decisions obtained by multi-classifiers. Through integrating two sides of multiple classification decisions, the classification is optimized and synthesized, thus the processing and results will be both powerful and stable. Experimental results show that the performance of the classification is greatly improved.