A new feature fusion method at decision level and its application

作     者：韩光 赵春霞 张浩峰 袁夏 

作者机构：College of Computer Science and TechnologyNanjing University of Science and Technology 

出 版 物：《Optoelectronics Letters》 (光电子快报（英文版）)

年 卷 期：2010年第6卷第2期

页      面：129-132页

核心收录：

学科分类：0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080203[工学-机械设计及理论] 0805[工学-材料科学与工程（可授工学、理学学位）] 0802[工学-机械工程] 0702[理学-物理学] 

基　　金：supported by the National Natural Science Foundation of China (Nos.60705020 and 90820306) 

主　　题：融合方法 决策层 应用 高斯混合模型 特征向量 概率计算 环境分类 GMM 

摘      要：To solve the problem that using only one feature is poor for the terrestrial environment classification,a new feature fusion method at decision level is proposed in this *** eigenvector is obtained by using a Gaussian mixture model(GMM) firstly,and the probabilities of the eigenvector belonging to a certain class of the texture and color are *** the probabilities are multiplied by different weights according to the contribution,and summed to get the maximal likelihood probability to achieve feature *** results demonstrate that the method in this paper is better than other current methods and the classification performance is superior to a single feature obviously.