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An Approach of Passive Vehicle Type Recognition by Acoustic Signal Based on SVM
Qi Xiao xuan
Ji Jian wei
Han Xiao wei
Yuan Zhong hu
3rd International Conference on Genetic and Evolutionary Computing, China,Guangxi Zhuang Autonomous Region,Guilin, 2009-10-14 to 2009-10-16.
An approach of power spectrum estimation is utilized to extract the feature vectors from acoustic signal radiated from different types of moving vehicles. A method of feature selection based on principal component analysis (PCA) is proposed to reconstruct effective feature vectors via dimension reduction. The classification of three typical targets is achieved by supported vector machine (SVM). Experiment results show that the approach presented in the paper for automatic recognition of vehicle type is effective.
vehicle recognition; SVM; acoustic signal; power spectrum estimation
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