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Multiple Kernel based KNN Classifiers for Vehicle Classification

by Pradeep Kumar Mishra, Biplab Banerjee
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 71 - Number 6
Year of Publication: 2013
Authors: Pradeep Kumar Mishra, Biplab Banerjee
10.5120/12359-8673

Pradeep Kumar Mishra, Biplab Banerjee . Multiple Kernel based KNN Classifiers for Vehicle Classification. International Journal of Computer Applications. 71, 6 ( June 2013), 1-7. DOI=10.5120/12359-8673

@article{ 10.5120/12359-8673,
author = { Pradeep Kumar Mishra, Biplab Banerjee },
title = { Multiple Kernel based KNN Classifiers for Vehicle Classification },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 71 },
number = { 6 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume71/number6/12359-8673/ },
doi = { 10.5120/12359-8673 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:34:46.958774+05:30
%A Pradeep Kumar Mishra
%A Biplab Banerjee
%T Multiple Kernel based KNN Classifiers for Vehicle Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 71
%N 6
%P 1-7
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The problem of vehicle classification has been addressed in this correspondence. Vehicle classification is a difficult task due to near similarity among various types vehicle features. Spectral properties of the image and near similarity between the front side of different vehicles makes the generalization process even more difficult. Here a multiple kernel based k-nearest neighbor classifier has been designed to improve the classification accuracy. After extracting the frames from the traffic video, vehicles are detected using background subtraction method. Then a wavelet and interest point based feature extraction step is carried out for each detected vehicle. Final classification is carried out using the newly proposed multiple kernel based k-nearest neighbor( KNN) algorithm. Experiments on several real time data-sets establish the higher accuracy of the proposed method in comparison to three well-known state of the art classification techniques.

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Index Terms

Computer Science
Information Sciences

Keywords

Classification Machine Learning Kernel MKL

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