By Topic

Real-time recognition system of traffic light in urban environment

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Zixing Cai ; Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China ; Yi Li ; Mingqin Gu

Detection of arrow traffic light is a focal point research in autonomous vehicle, and in urban environment it is the basic technique. However, most researches mainly concern the circular traffic lights. A novel algorithm is proposed in this paper to resolve the problems of detection and recognition of arrow traffic lights. Two sub-modules, detection module and recognition module, are introduced in the main framework. In detection submodule, the color space conversion, binarization and morphology features filtering methods are performed to get the regions of candidates of blackboards. For getting the regions of arrow of traffic lights, segmentation based on the YCbCr color space is used in the cropping image, which is cropped from original image by the region of blackboard. In recognition sub-module, Gabor wavelet transform and 2D independent component analysis(2DICA) are used to extract traffic light candidate's features for features of the arrow traffic lights. A library for recognition has been built, and experimental results show that rate of recognition exceeds 91%.

Published in:

Computational Intelligence for Security and Defence Applications (CISDA), 2012 IEEE Symposium on

Date of Conference:

11-13 July 2012