Real-time traffic light detection on resource-limited mobile platform

Yi Tung Chiu*, Duan Yu Chen, Jun-Wei Hsieh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

Given the rapid expansion of car ownership worldwide, vehicle safety is an increasingly critical issue in the automobile industry. The reduced cost of intelligent mobile phones has made it economically feasible to develop intelligent systems for visual-based event detection for forward collision avoidance and mitigation. In this work, a real-time traffic red light recognition is proposed under mobile platforms. The proposed method consists of real-time traffic lights localization via image down-sampling, circular regions detection and further traffic lights recognition. Hough Transform is modified to fast localize the traffic light candidates. Finally, a strong classifier is made from multiple weak features is employed for further verifications. In the experiment, the detection rate can achieve above 70%. This shows that our proposed traffic light recognition can be applied in real world environments.

Original languageEnglish
Title of host publicationDigest of Technical Papers - IEEE International Conference on Consumer Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages211-212
Number of pages2
ISBN (Electronic)9781479938308
DOIs
StatePublished - 18 Sep 2014
Event1st IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2014 - Taipei, Taiwan
Duration: 26 May 201428 May 2014

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
ISSN (Print)0747-668X

Conference

Conference1st IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2014
CountryTaiwan
CityTaipei
Period26/05/1428/05/14

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