Title :
Small-shaped space target recognition based on wavelet decomposition and support vector machine
Author :
Zhu, Feng-Yun ; Qin, Shi-Yin
Author_Institution :
Beihang Univ., Beijing
Abstract :
A kind of method for small-shaped space target recognition was proposed in this paper based on feature extraction with wavelet decomposition and formative support vector machine (FSVM) with sequential minimal optimization (SMO) algorithm. Firstly, the significance and characteristics of space target recognition were discussed and a two-stage recognition strategy was designed. And then aiming at the characteristics of small-shaped space target recognition, a new method was implemented based on feature extraction with wavelet decomposition and FSVM with SMO algorithm. Simulation results show the good performance of the algorithm proposed in this paper: the correct rate is more than 97% within 1360 simulation samples of ten classes of small shaped space targets; meanwhile the algorithm is characterized with high speed of near real time in both implementation of training and testing.
Keywords :
feature extraction; object recognition; optimisation; support vector machines; wavelet transforms; feature extraction; sequential minimal optimization algorithm; small-shaped space target recognition; support vector machine; wavelet decomposition; Character recognition; Feature extraction; Machine learning; Optimization methods; Pattern recognition; Radar signal processing; Signal processing algorithms; Support vector machines; Target recognition; Wavelet analysis; SMO; SVM; Small-shaped space target; feature extraction; target recognition; wavelet decomposition;
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1065-1
Electronic_ISBN :
978-1-4244-1066-8
DOI :
10.1109/ICWAPR.2007.4421653
