A novel method for image classification

Support Vector Machines have been extensively utilized in image classification due to their high performance. However, Support Vector Machines treats each training sample equally without the consideration of their different influences on constructing decision surface, the generalization performance might be degraded. In this paper, a novel fuzzy classification approach integrating self-organizing maps into Support Vector Machines is proposed to improve the generalization performance. The experimental results show the effectiveness and efficiency of the proposed classification approach based on Fuzzy Support Vector Machines.