Application of support vector machine and quantum genetic algorithm in infrared target recognition

Hongliang Wang; Yangwen Huang; Haifei Ding

doi:10.1117/12.866715

19 August 2010 Application of support vector machine and quantum genetic algorithm in infrared target recognition

Hongliang Wang, Yangwen Huang, Haifei Ding

Proceedings Volume 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering; 78201O (2010) https://doi.org/10.1117/12.866715
Event: International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 2010, Xi'an, China

Abstract

In this paper, a kind of classifier based on support vector machine (SVM) is designed for infrared target recognition. In allusion to the problem how to choose kernel parameter and error penalty factor, quantum genetic algorithm (QGA) is used to optimize the parameters of SVM model, it overcomes the shortcoming of determining its parameters after trial and error in the past. Classification experiments of infrared target features extracted by this method show that the convergence speed is fast and the rate of accurate recognition is high.

Citation Download Citation

Hongliang Wang, Yangwen Huang, and Haifei Ding "Application of support vector machine and quantum genetic algorithm in infrared target recognition", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78201O (19 August 2010); https://doi.org/10.1117/12.866715

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