A Method of Aircraft Image Target Recognition Based on Modified PCA Features and SVM

摘要：

Automatic target recognition(ATR) is an important task in image application. This paper concentrates on two key subroutines of ATR system: Dimensionality reduction and Classifier. After pretreatment on original features a self-organizing neural network trained with the Hebbian rule is used to extract the principal component features. Then a classifier based on Directed Acyclic Graph Support Vector Machines (DAGSVM) is adopted to recognize more than two types of aircraft targets. The experiment results show the proposed method achieves better subset features and higher recognition rate.

关键词： target recognition dimensionality reduction feature eztraction feature selection PCA,SVM classifier design

作者: Donghe Wang Xin He Wei Zhonghui Huilong Yu

作者单位: Changchun Institute of Optics Fine Mechanics and Physics,Chinese Academy of Science,Changchun 130033 Changchun Institute of Optics Fine Mechanics and Physics,Chinese Academy of Science,Changchun 130033

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 3405-3409

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）