基于独立成分分析和模糊支持向量机的车标识别新方法  

A novel method for vehicle-logo recognition based on independent component analysis and fuzzy support vector machine

作　　者：孙娟红[1] 李文举[1] 冯宇[1] 韦丽华[1] 

机构地区：[1]辽宁师范大学计算机与信息技术学院,辽宁大连116081

出　　处：《微型机与应用》2011年第13期32-35,38,共5页Microcomputer & Its Applications

基　　金：辽宁省教育厅高等学校科研项目(L2010232)

摘　　要：提出了一种新的车标识别方法。首先,利用独立成分分析提取车标特征,然后,采用模糊支持向量机设计分类器进行车标识别。实验结果表明,与现有车标识别方法相比,该方法识别率高、速度快。A new vehicle-logo recognition method is proposed in this paper. Firstly, the feature of vehicle-logos is extracted by independent component analysis, and then the classifier for recognizing vehicle-logos is designed by fuzzy support vector machine. Experimental results show that the proposed method has higher accuracy and faster speed than the existing methods for vehicle-logo recognition.

关 键 词：车标识别 主成分分析 独立成分分析 模糊支持向量机 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]