Speed Limit Sign Detection Based On Gaussian Color Model And Template Matching

被引：7

作者：

Huang, Han ^{[1
]}

Hou, Ling-Ying ^{[2
]}

机构：

[1] Northeastern Univ, Coll Engn, Boston, MA 02115 USA

[2] Nanchang Inst Technol, Deans Off, Nanchang, Jiangxi, Peoples R China

来源：

2017 INTERNATIONAL CONFERENCE ON VISION, IMAGE AND SIGNAL PROCESSING (ICVISP) | 2017年

基金：

中国国家自然科学基金;

关键词：

Traffic sign detection; Gaussian color model; Thresholding segmentation; Image segmentation; RECOGNITION;

D O I：

10.1109/ICVISP.2017.30

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Traffic sign detection and recognition play crucial roles on the Intelligent Transportation System(ITS). Firstly, in YCbCr color space, color segmentation of the traffic scene images using Gaussian color model is calculated, and traffic sign regions are obtained. Secondly, the morphology processing is utilized on the segmented image to extract the candidate traffic signs with a rectangle region in the original image to be selected according as its shape property. Finally, template matching is applied for speed signs classification. The performance of the proposed method is evaluated on Norwegian speed limit signs in natural environment. Experiment results show that this algorithm can effectively improve the traffic sign detection efficiency, which is used in traffic signs recognition and tracking of intelligent vehicles.

引用

页码：118 / 122

页数：5

共 10 条

[1]

Barnes Nick, 2014, 10 IEEE INT C COMP V, V1, P778

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