Real-time driver drowsiness detection system based on PERCLOS and grayscale image processing

Jun Juh Yan; Hang Hong Kuo; Ying Fan Lin; Teh Lu Liao

doi:10.1109/IS3C.2016.72

Real-time driver drowsiness detection system based on PERCLOS and grayscale image processing

Jun Juh Yan, Hang Hong Kuo, Ying Fan Lin, Teh Lu Liao

Department of Engineering Science

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

59 Citations (Scopus)

Abstract

This study develops a real-time drowsiness detection system based on grayscale image processing and PERCLOS to determine if the driver is fatigued. The proposed system comprises three parts: first, it calculates the approximate position of the driver's face in grayscale images, and then uses a small template to analyze the eye positions, second, it uses the data from the previous step and PERCLOS to establish a fatigue model, and finally, based on the driver's personal fatigue model, the system continuously monitors the driver's state. Once the driver exhibits fatigue, the system alerts the driver to stop driving and take a rest.

Original language	English
Title of host publication	Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	243-246
Number of pages	4
ISBN (Electronic)	9781509030712
DOIs	https://doi.org/10.1109/IS3C.2016.72
Publication status	Published - 2016 Aug 16
Event	2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016 - Xi'an, China Duration: 2016 Jul 4 → 2016 Jul 6

Publication series

Name	Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016

Other

Other	2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016
Country/Territory	China
City	Xi'an
Period	16-07-04 → 16-07-06

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Networks and Communications
Computer Science Applications
Energy Engineering and Power Technology
Control and Systems Engineering
Control and Optimization

Access to Document

10.1109/IS3C.2016.72

Cite this

Yan, J. J., Kuo, H. H., Lin, Y. F., & Liao, T. L. (2016). Real-time driver drowsiness detection system based on PERCLOS and grayscale image processing. In Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016 (pp. 243-246). Article 7545182 (Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IS3C.2016.72

Yan, Jun Juh ; Kuo, Hang Hong ; Lin, Ying Fan et al. / Real-time driver drowsiness detection system based on PERCLOS and grayscale image processing. Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 243-246 (Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016).

@inproceedings{b7234b90aa7e4b0aae9e88c552d7104e,

title = "Real-time driver drowsiness detection system based on PERCLOS and grayscale image processing",

abstract = "This study develops a real-time drowsiness detection system based on grayscale image processing and PERCLOS to determine if the driver is fatigued. The proposed system comprises three parts: first, it calculates the approximate position of the driver's face in grayscale images, and then uses a small template to analyze the eye positions, second, it uses the data from the previous step and PERCLOS to establish a fatigue model, and finally, based on the driver's personal fatigue model, the system continuously monitors the driver's state. Once the driver exhibits fatigue, the system alerts the driver to stop driving and take a rest.",

author = "Yan, {Jun Juh} and Kuo, {Hang Hong} and Lin, {Ying Fan} and Liao, {Teh Lu}",

year = "2016",

month = aug,

day = "16",

doi = "10.1109/IS3C.2016.72",

language = "English",

series = "Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016",

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

pages = "243--246",

booktitle = "Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016",

address = "United States",

note = "2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016 ; Conference date: 04-07-2016 Through 06-07-2016",

}

Yan, JJ, Kuo, HH, Lin, YF & Liao, TL 2016, Real-time driver drowsiness detection system based on PERCLOS and grayscale image processing. in Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016., 7545182, Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016, Institute of Electrical and Electronics Engineers Inc., pp. 243-246, 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016, Xi'an, China, 16-07-04. https://doi.org/10.1109/IS3C.2016.72

Real-time driver drowsiness detection system based on PERCLOS and grayscale image processing. / Yan, Jun Juh; Kuo, Hang Hong; Lin, Ying Fan et al.
Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 243-246 7545182 (Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016).

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

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N2 - This study develops a real-time drowsiness detection system based on grayscale image processing and PERCLOS to determine if the driver is fatigued. The proposed system comprises three parts: first, it calculates the approximate position of the driver's face in grayscale images, and then uses a small template to analyze the eye positions, second, it uses the data from the previous step and PERCLOS to establish a fatigue model, and finally, based on the driver's personal fatigue model, the system continuously monitors the driver's state. Once the driver exhibits fatigue, the system alerts the driver to stop driving and take a rest.

AB - This study develops a real-time drowsiness detection system based on grayscale image processing and PERCLOS to determine if the driver is fatigued. The proposed system comprises three parts: first, it calculates the approximate position of the driver's face in grayscale images, and then uses a small template to analyze the eye positions, second, it uses the data from the previous step and PERCLOS to establish a fatigue model, and finally, based on the driver's personal fatigue model, the system continuously monitors the driver's state. Once the driver exhibits fatigue, the system alerts the driver to stop driving and take a rest.

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BT - Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016

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Yan JJ, Kuo HH, Lin YF, Liao TL. Real-time driver drowsiness detection system based on PERCLOS and grayscale image processing. In Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 243-246. 7545182. (Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016). doi: 10.1109/IS3C.2016.72

Real-time driver drowsiness detection system based on PERCLOS and grayscale image processing

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