Automatic vehicle classification using linked visual words

Nattachai Watcharapinchai; Supavadee Aramvith; Supakorn Siddhichai

doi:10.1117/1.JEI.26.4.043009

25 July 2017 Automatic vehicle classification using linked visual words

Nattachai Watcharapinchai, Supavadee Aramvith, Supakorn Siddhichai

Author Affiliations +

Journal of Electronic Imaging, Vol. 26, Issue 4, 043009 (July 2017). https://doi.org/10.1117/1.JEI.26.4.043009

Abstract

An improvement in the method of automatic vehicle classification is investigated. The challenges are to correctly classify vehicles regardless of changes in illumination, differences in points of view of the camera, and variations in the types of vehicles. Our proposed appearance-based feature extraction algorithm is called linked visual words (LVWs) and is based on the existing technique bag-of-visual word (BoVW) with the addition of spatial information to improve accuracy of classification. In addition, to prevent over-fitting due to a large number of LVWs, four common sampling techniques with LVWs are investigated. Our results suggest that the sampling of LVWs using TF-IDF with grouping improved the accuracy of classification for the test dataset. In summary, the proposed system is able to classify nine types of vehicles and work with surveillance cameras in real-world scenarios. The classification accuracy of the proposed system is 5.58% and 4.27% higher on average for three datasets when compared with BoVW + SVM and Lenet-5, respectively.

Citation Download Citation

Nattachai Watcharapinchai, Supavadee Aramvith, and Supakorn Siddhichai "Automatic vehicle classification using linked visual words," Journal of Electronic Imaging 26(4), 043009 (25 July 2017). https://doi.org/10.1117/1.JEI.26.4.043009

Received: 21 February 2017; Accepted: 29 June 2017; Published: 25 July 2017

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available