Road Vehicle Classification Based on Extreme Learning Machine

DOI

10.2991/eeic-13.2013.101How to use a DOI?

Keywords

Vehicle classification; Extreme learning machine; Invariant moments; Edge detection

Abstract

Road vehicle classification plays an important role in traffic surveillance, traffic security, and transportation management systems. This paper proposes a novel vehicle classification algorithm based on extreme learning machine. Invariant moments and horizontal edge features are extracted to classify vehicles into sedan, bus and van truck. Experimental results show that the proposed method can satisfactorily achieve vehicle classification at very fast training speed.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yan-shuang Hao
AU  - Yi-xin Yin
AU  - Jin-hui Lan
PY  - 2013/12
DA  - 2013/12
TI  - Road Vehicle Classification Based on Extreme Learning Machine
BT  - Proceedings of the 3rd International Conference on Electric and Electronics
PB  - Atlantis Press
SP  - 430
EP  - 433
SN  - 1951-6851
UR  - https://doi.org/10.2991/eeic-13.2013.101
DO  - 10.2991/eeic-13.2013.101
ID  - Hao2013/12
ER  -