Real-Time traffic light detection using color density

Tai Huu Phuong Tran; Cuong Cao Pham; Tien Phuoc Nguyen; Tin Trung Duong; Jae Wook Jeon

doi:10.1109/ICCE-Asia.2016.7804791

Real-Time traffic light detection using color density

Tai Huu Phuong Tran
, Cuong Cao Pham
, Tien Phuoc Nguyen
, Tin Trung Duong
, Jae Wook Jeon

Department of Semiconductor Systems Engineering

Sungkyunkwan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

21 Scopus citations

Abstract

Autonomous driving cars have become a trend in the vehicle industry. Numerous driver assistance systems (DAS) have been introduced to support these automatic cars. Among these DAS methods, traffic light detection (TLD) plays a significant role. This paper proposes a method to detect traffic lights (TLs) using color density identification (CD). The system receives an RGB image as an input and produces the traffic light state (red, yellow, green or no Signal) of the scene. The algorithm has three stages: clustering, filtering, and state identification. Experiments were conducted on both highways and in urban areas in Korea. The results achieved around 95% accuracy on highways and 85% in urban areas. Furthermore, the proposed algorithm is able to run in real-Time with 60FPS.

Original language	English
Title of host publication	2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509027439
DOIs	https://doi.org/10.1109/ICCE-Asia.2016.7804791
State	Published - 3 Jan 2017
Event	2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016 - Seoul, Korea, Republic of Duration: 26 Oct 2016 → 28 Oct 2016

Publication series

Name	2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016

Conference

Conference	2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016
Country/Territory	Korea, Republic of
City	Seoul
Period	26/10/16 → 28/10/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Color density
Real-Time application
Traffic light detection

Access to Document

10.1109/ICCE-Asia.2016.7804791

Cite this

Tran, T. H. P., Pham, C. C., Nguyen, T. P., Duong, T. T., & Jeon, J. W. (2017). Real-Time traffic light detection using color density. In 2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016 Article 7804791 (2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-Asia.2016.7804791

@inproceedings{57930be2c9d14a809a0e29631955bbed,

title = "Real-Time traffic light detection using color density",

abstract = "Autonomous driving cars have become a trend in the vehicle industry. Numerous driver assistance systems (DAS) have been introduced to support these automatic cars. Among these DAS methods, traffic light detection (TLD) plays a significant role. This paper proposes a method to detect traffic lights (TLs) using color density identification (CD). The system receives an RGB image as an input and produces the traffic light state (red, yellow, green or no Signal) of the scene. The algorithm has three stages: clustering, filtering, and state identification. Experiments were conducted on both highways and in urban areas in Korea. The results achieved around 95\% accuracy on highways and 85\% in urban areas. Furthermore, the proposed algorithm is able to run in real-Time with 60FPS.",

keywords = "Color density, Real-Time application, Traffic light detection",

author = "Tran, \{Tai Huu Phuong\} and Pham, \{Cuong Cao\} and Nguyen, \{Tien Phuoc\} and Duong, \{Tin Trung\} and Jeon, \{Jae Wook\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016 ; Conference date: 26-10-2016 Through 28-10-2016",

year = "2017",

month = jan,

day = "3",

doi = "10.1109/ICCE-Asia.2016.7804791",

language = "English",

series = "2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016",

}

Tran, THP, Pham, CC, Nguyen, TP, Duong, TT & Jeon, JW 2017, Real-Time traffic light detection using color density. in 2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016., 7804791, 2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016, Seoul, Korea, Republic of, 26/10/16. https://doi.org/10.1109/ICCE-Asia.2016.7804791

Real-Time traffic light detection using color density. / Tran, Tai Huu Phuong; Pham, Cuong Cao; Nguyen, Tien Phuoc et al.
2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7804791 (2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Real-Time traffic light detection using color density

AU - Tran, Tai Huu Phuong

AU - Pham, Cuong Cao

AU - Nguyen, Tien Phuoc

AU - Duong, Tin Trung

AU - Jeon, Jae Wook

PY - 2017/1/3

Y1 - 2017/1/3

N2 - Autonomous driving cars have become a trend in the vehicle industry. Numerous driver assistance systems (DAS) have been introduced to support these automatic cars. Among these DAS methods, traffic light detection (TLD) plays a significant role. This paper proposes a method to detect traffic lights (TLs) using color density identification (CD). The system receives an RGB image as an input and produces the traffic light state (red, yellow, green or no Signal) of the scene. The algorithm has three stages: clustering, filtering, and state identification. Experiments were conducted on both highways and in urban areas in Korea. The results achieved around 95% accuracy on highways and 85% in urban areas. Furthermore, the proposed algorithm is able to run in real-Time with 60FPS.

AB - Autonomous driving cars have become a trend in the vehicle industry. Numerous driver assistance systems (DAS) have been introduced to support these automatic cars. Among these DAS methods, traffic light detection (TLD) plays a significant role. This paper proposes a method to detect traffic lights (TLs) using color density identification (CD). The system receives an RGB image as an input and produces the traffic light state (red, yellow, green or no Signal) of the scene. The algorithm has three stages: clustering, filtering, and state identification. Experiments were conducted on both highways and in urban areas in Korea. The results achieved around 95% accuracy on highways and 85% in urban areas. Furthermore, the proposed algorithm is able to run in real-Time with 60FPS.

KW - Color density

KW - Real-Time application

KW - Traffic light detection

UR - https://www.scopus.com/pages/publications/85011076369

U2 - 10.1109/ICCE-Asia.2016.7804791

DO - 10.1109/ICCE-Asia.2016.7804791

M3 - Conference contribution

AN - SCOPUS:85011076369

T3 - 2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016

BT - 2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016

Y2 - 26 October 2016 through 28 October 2016

ER -

Tran THP, Pham CC, Nguyen TP, Duong TT, Jeon JW. Real-Time traffic light detection using color density. In 2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7804791. (2016 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2016). doi: 10.1109/ICCE-Asia.2016.7804791

Real-Time traffic light detection using color density

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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