It is a difficult problem to make drivers drowsiness detection meet the needs of real time in embedded system; meanwhile, there are still some unsolved problems like drivers’ head tilted and size of eye image not large enough. This paper proposes an efficient method to solve these problems for eye state identification of drivers’ drowsiness detection in embedded system which based on image processing techniques. This method break traditional way of drowsiness detection to make it real time, it utilizes face detection and eye detection to initialize the location of driver’s eyes; after that an object tracking method is used to keep track of the eyes; finally, we can identify drowsiness state of driver with PERCLOS by identified eye state. Experiment results show that it makes good agreement with analysis.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Drivers drowsiness detection in embedded system


    Contributors:
    Tianyi Hong, (author) / Huabiao Qin, (author)


    Publication date :

    2007-12-01


    Size :

    300757 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Drowsiness Detection for Drivers using IoT

    S S, Saranya / M N, Kavitha / M, Sivasenthil et al. | IEEE | 2023



    A Smartphone-Based Drowsiness Detection and Warning System for Automotive Drivers

    Dasgupta, Anirban / Rahman, Daleef / Routray, Aurobinda | IEEE | 2019


    Drowsiness Detection System

    CRONJE JACO / HOUGH JOHANN EPHRAIM | European Patent Office | 2021

    Free access

    Enhancing Road Safety with AdaBoost-Based Drowsiness Detection for Drivers

    Mahmud, Tanjim / Tripura, Sajib / Karim, Md. Adnan Ul et al. | Springer Verlag | 2024