Laser & Optoelectronics Progress, Volume. 61, Issue 22, 2215005(2024)

Fatigue Driving Detection Under Low Illumination Using Image Enhancement and Facial State Recognition

Yang Zhao1,2, Jialong Miao1、*, Xuefeng Liu1, Jincheng Zhao3, and Sen Xu1,2
Author Affiliations
  • 1The College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang 110142, Liaoning , China
  • 2Key Laboratory of Intelligent Technology for Chemical Process Industry of Liaoning Province, Shenyang 110142, Liaoning , China
  • 3The College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, Liaoning , China
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    References(31)

    [7] Zhang Z W. Research on the detection method of abnormal driving behavior based on machine vision[D](2020).

    [8] Ao B Q, Yang S, Linghu J Q et al. Design of fatigue driving detection system based on cascaded neural network[J]. Journal of System Simulation, 34, 323-333(2022).

    [10] Lü X L, Liu X F, Bai Y Q. Research on driving fatigue detection based on SSD muti-factor fusion[J]. Electronic Measurement Technology, 45, 138-143(2022).

    [20] Cui X F. Research on several issues about face keypoints detection[D](2019).

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    Yang Zhao, Jialong Miao, Xuefeng Liu, Jincheng Zhao, Sen Xu. Fatigue Driving Detection Under Low Illumination Using Image Enhancement and Facial State Recognition[J]. Laser & Optoelectronics Progress, 2024, 61(22): 2215005

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    Paper Information

    Category: Machine Vision

    Received: Feb. 20, 2024

    Accepted: Mar. 25, 2024

    Published Online: Nov. 19, 2024

    The Author Email: Jialong Miao (igxiaodingdang@163.com)

    DOI:10.3788/LOP240711

    CSTR:32186.14.LOP240711

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