Multiple templates matching for vehicle''''s classification based on dynamic time warping
基于动态时间弯曲的多模板匹配车型分类

A vehicle's frequency-response curve is determined by its velocity,structural framework and the relative location to an inductive coil detector.As the frequency-response curves of vehicles of the same type are varied in length, a novel classification method based on the dynamic-time-warping (DTW) algorithm is proposed.After a pretreatment on the obtained frequency-response curves,multiple curves are selected as vehicle classification-templates for DTW algorithm and the optimal clustering method.This will improve the classification properties of the single-template matching method. Next,we determine the dissimilarity-indices and their ranges for the vehicles of the same type.Finally,the classification result is obtained by matching the sample curve to the multiple templates using DTW algorithm.A simulation is given to illustrate the advantage of the method