Real-time vehicle color identification for surveillance videos

Chih Yang Lin; Cheng Hao Yeh; Chia Hung Yeh

doi:10.1109/CONIELECOMP.2014.6808568

Real-time vehicle color identification for surveillance videos

Chih Yang Lin^*, Cheng Hao Yeh, Chia Hung Yeh

^*Corresponding author for this work

Research output: Contribution to conference › Paper › peer-review

7 Citations (Scopus)

Abstract

Vehicles are one of the main detection targets of the traffic and security video surveillance system. In this paper, we propose an automatic vehicle color identification method for vehicle classification. The main idea of the proposed scheme is to divide a vehicle into a hierarchical coarse-to-fine structure to extract its wheels, windows, main body, and other auto parts. In the proposed method, the main body alone is used by a support vector machine (SVM) for classification. Experimental results show that the proposed scheme is efficient and effective and the proposed vehicle color identification is suitable for real-time surveillance applications.

Original language	English
Pages	59-64
Number of pages	6
DOIs	https://doi.org/10.1109/CONIELECOMP.2014.6808568
Publication status	Published - 2014
Externally published	Yes
Event	24th International Conference on Electronics, Communications and Computers, CONIELECOMP 2014 - Cholula, Mexico Duration: 2014 Feb 26 → 2014 Feb 28

Conference

Conference	24th International Conference on Electronics, Communications and Computers, CONIELECOMP 2014
Country/Territory	Mexico
City	Cholula
Period	2014/02/26 → 2014/02/28

Keywords

support vector machine
tree structure
vehicle color classification

ASJC Scopus subject areas

Computer Networks and Communications
Electrical and Electronic Engineering

Access to Document

10.1109/CONIELECOMP.2014.6808568

Cite this

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title = "Real-time vehicle color identification for surveillance videos",

abstract = "Vehicles are one of the main detection targets of the traffic and security video surveillance system. In this paper, we propose an automatic vehicle color identification method for vehicle classification. The main idea of the proposed scheme is to divide a vehicle into a hierarchical coarse-to-fine structure to extract its wheels, windows, main body, and other auto parts. In the proposed method, the main body alone is used by a support vector machine (SVM) for classification. Experimental results show that the proposed scheme is efficient and effective and the proposed vehicle color identification is suitable for real-time surveillance applications.",

keywords = "support vector machine, tree structure, vehicle color classification",

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doi = "10.1109/CONIELECOMP.2014.6808568",

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AU - Lin, Chih Yang

AU - Yeh, Cheng Hao

AU - Yeh, Chia Hung

PY - 2014

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N2 - Vehicles are one of the main detection targets of the traffic and security video surveillance system. In this paper, we propose an automatic vehicle color identification method for vehicle classification. The main idea of the proposed scheme is to divide a vehicle into a hierarchical coarse-to-fine structure to extract its wheels, windows, main body, and other auto parts. In the proposed method, the main body alone is used by a support vector machine (SVM) for classification. Experimental results show that the proposed scheme is efficient and effective and the proposed vehicle color identification is suitable for real-time surveillance applications.

AB - Vehicles are one of the main detection targets of the traffic and security video surveillance system. In this paper, we propose an automatic vehicle color identification method for vehicle classification. The main idea of the proposed scheme is to divide a vehicle into a hierarchical coarse-to-fine structure to extract its wheels, windows, main body, and other auto parts. In the proposed method, the main body alone is used by a support vector machine (SVM) for classification. Experimental results show that the proposed scheme is efficient and effective and the proposed vehicle color identification is suitable for real-time surveillance applications.

KW - support vector machine

KW - tree structure

KW - vehicle color classification

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T2 - 24th International Conference on Electronics, Communications and Computers, CONIELECOMP 2014

Y2 - 26 February 2014 through 28 February 2014

ER -

Real-time vehicle color identification for surveillance videos

Abstract

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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