DocumentCode :
135442
Title :
Real-time vehicle color identification for surveillance videos
Author :
Chih-Yang Lin ; Cheng-Hao Yeh ; Chia-Hung Yeh
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Asia Univ., Taichung, Taiwan
fYear :
2014
fDate :
26-28 Feb. 2014
Firstpage :
59
Lastpage :
64
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 :
image classification; image colour analysis; support vector machines; traffic engineering computing; video surveillance; SVM; automatic vehicle color identification; hierarchical coarse-to-fine structure; real-time vehicle color identification; security video surveillance system; support vector machine; traffic system; vehicle classification; Accuracy; Colored noise; Feature extraction; Histograms; Image color analysis; Support vector machines; Vehicles; support vector machine; tree structure; vehicle color classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Communications and Computers (CONIELECOMP), 2014 International Conference on
Conference_Location :
Cholula
Print_ISBN :
978-1-4799-3468-3
Type :
conf
DOI :
10.1109/CONIELECOMP.2014.6808568
Filename :
6808568
Link To Document :
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