Vehicle Color Recognition in The Surveillance with Deep Convolutional Neural Networks

DOI

10.2991/jimet-15.2015.147How to use a DOI?

Keywords

Vehicle Color Recognition, Deep Convolutional Nerual Networks, network in network.

Abstract

Vehicle information extraction is the key means in Intelligent Transportation System (ITS). Color plays an important role in vehicle recognition. The main challenge of vehicle color recognition is to find the dominant color. In this paper, we propose a color recognition method using convolutional neural network. We train the classifier with the network structure „NIN to increase the classification accuracy. The experiments are validated on our dataset and extra data, which are collected from city surveillance equipment. The proposed method outperforms other competing color recognition methods.

Copyright

© 2015, 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  - Boyang Su
AU  - Jie Shao
AU  - Jianying Zhou
AU  - Xiaoteng Zhang
AU  - Lin Mei
PY  - 2015/12
DA  - 2015/12
TI  - Vehicle Color Recognition in The Surveillance with Deep Convolutional Neural Networks
BT  - Proceedings of the 2015 Joint International Mechanical, Electronic and Information Technology Conference
PB  - Atlantis Press
SP  - 790
EP  - 793
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimet-15.2015.147
DO  - 10.2991/jimet-15.2015.147
ID  - Su2015/12
ER  -