Vehicle classification using support vector machines and k-means clustering

Hsun-Jung Cho, Rih Jin Li, Hsia Lee, Jennifer Yuh Jen Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This investigation involves the combination of support vector machines (SVM) and k-means clustering implemented on radar signal. SVM classifier based on k-means algorithm has an advance for classifying unlabeled data. To classify the vehicle types automatically, the combined method is implemented with radar signals. This paper proposed a classifier training algorithm based on SVM and k-means clustering as follows (i) using the k-means algorithm to label the input feature data extracted from radar signal into two subsets, (ii) train SVM with labeled data, and (iii) classify unidentified radar signal into large vehicle or small vehicle with the trained classifier. Training features of radar signal includes (i) signal volume and (ii) sum of signal variations, both in frequency domain. These features are taken as system input, while vehicle types as system output. The proposed algorithm is implemented and demonstrated with real FMCW radar signals. With the numerical experiment, satisfying result is obtained.

Original languageEnglish
Title of host publicationComputational Methods in Science and Engineering - Advances in Computational Science, Lectures Presented at the Int. Conference on Computational Methods in Science and Engineering 2008, ICCMSE 2008
Pages449-452
Number of pages4
DOIs
StatePublished - 1 Dec 2009
Event6th International Conference on Computational Methods in Sciences and Engineering 2008, ICCMSE 2008 - Hersonissos, Crete, Greece
Duration: 25 Sep 200830 Sep 2008

Publication series

NameAIP Conference Proceedings
Volume1148 2
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference6th International Conference on Computational Methods in Sciences and Engineering 2008, ICCMSE 2008
CountryGreece
CityHersonissos, Crete
Period25/09/0830/09/08

Keywords

  • fc-means Clustering
  • Support Vector Machines (SVM)
  • Vehicle Classification

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