Title :
A new method of target recognition based on Rough Set and Support Vector Machine
Author :
Guo, Zhi-Jun ; He, Xin ; Wei, Zhong-hui ; Liang, Guo-long
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: Pre-treatment and design of classifier. In the pre-treatment subroutine, a new method based on Rough Set (RS) is proposed to partition the original sample set into some subsets and calculate their class membership, so that some samples can be chosen by class membership to be trained. After pre-treatment, an iterative algorithm based on Rough Set and Support Vector Machines (IRSSVM) is introduced to design a classifier for recognizing two types of targets. The experiment results show that IRSSVM needs less training time and the classifier is simpler and has more generalization and higher recognition rate.
Keywords :
image recognition; iterative methods; object detection; pattern classification; rough set theory; support vector machines; automatic target recognition; class membership; classifier design; image application; iterative algorithm; pre-treatment; recognition rate; rough set theory; subsets; support vector machine; training time; Algorithm design and analysis; Data mining; Fuzzy set theory; Helium; Iterative algorithms; Physics; Set theory; Support vector machine classification; Support vector machines; Target recognition; class membership; data partition; fuzzy theory; iterative algorithm; rough set; sample sorting; support vector machine; target recognition;
Conference_Titel :
Image Analysis and Signal Processing (IASP), 2010 International Conference on
Conference_Location :
Zhejiang
Print_ISBN :
978-1-4244-5554-6
Electronic_ISBN :
978-1-4244-5556-0
DOI :
10.1109/IASP.2010.5476053