Research on Unmanned Vehicle Traffic Signal Recognition Technology

Author

Wang Hong-jiang ; Ren Na ; Zhang Wen-Qiang ; Zhao Ting-ting ; Lun-feng, Cui ; Rong-xue, Zhang ; Feng, Tian

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Shenyang Inst. of Eng., Shenyang, China

Volume

2

fYear

2010

fDate

13-14 Oct. 2010

Firstpage

298

Lastpage

301

Abstract

A method for the traffic signal recognition of his color space and bp neural network algorithm. First convert the traffic signal images from RGB space to HSI space, and then extracted H Component characteristics from HSI space in the traffic signal images, according to the Component histogram, determine the signal color. Finally, BP neural network is applied for the traffic signal lights recognition. It´s demonstrated by practice that BP neural network can be used for fast and efficient recognition of traffic signal with high accuracy and practical value.

Keywords

backpropagation; image colour analysis; image recognition; neural nets; remotely operated vehicles; statistical analysis; traffic engineering computing; BP neural network; H component characteristics; HSI color space; RGB space; component histogram; signal color; traffic signal image; traffic signal light recognition; unmanned vehicle; Algorithm design and analysis; Artificial neural networks; Histograms; Image color analysis; Image recognition; Signal processing algorithms; Training; bp neural network algorithm; hsi color space; statistical histogram; the traffic signal;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on

Conference_Location

Changsha

Print_ISBN

978-1-4244-8333-4

Type

conf

DOI

10.1109/ISDEA.2010.182

Filename

5743426