Title :
A method of aircraft image target recognition based on modified PCA features and SVM
Author :
Wang, Donghe ; He, Xin ; Zhonghui, Wei ; Yu, Huilong
Author_Institution :
Changchun Inst. of Opt. Fine Mech. & Phys., Chinese Acad. of Sci., Changchun, China
Abstract :
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.
Keywords :
Hebbian learning; aircraft; feature extraction; image classification; neural nets; principal component analysis; support vector machines; ATR; Hebbian rule; SVM; aircraft image target recognition; classifier; dimensionality reduction; directed acyclic graph support vector machines; feature extraction; modified PCA; principal component analysis; self-organizing neural network; Aerospace electronics; Aircraft; Algorithms; Data mining; Feature extraction; Instruments; Neural networks; Principal component analysis; Support vector machines; Target recognition; PCA; SVM; classifier design; dimensionality reduction; feature extraction; feature selection; target recognition;
Conference_Titel :
Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3863-1
Electronic_ISBN :
978-1-4244-3864-8
DOI :
10.1109/ICEMI.2009.5274100
