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An image processing-based system proposal for real-time detection of drowsiness from a vehicle driver's eye movements
2021
Academic Perspective Procedia
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This study proposes a real-time image processing-based system for recognizing the drowsiness face expression of the vehicle driver. ...
This system, after detecting drowsiness eye, give audible alert the vehicle driver to stay awake throughout the driving journey. ...
In these systems, which are controlling the state of drowsiness of the driver through a webcam with night vision to track the driver in real time and when drowsiness is detected, the system will send a ...
doi:10.33793/acperpro.04.01.15
fatcat:7dhqv23xtzbvho6kfztwlza3vu
IMAGE AND BRAIN SIGNAL PROCESSING BASED DROWSINESS DETECTING AND ALARMING SYSTEM
2019
MATTER International Journal of Science and Technology
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A system that automatically detects drowsiness of the driver in real time using computer vision is proposed. ...
This multi-model technique makes use of Signal and Image processing for effectively detecting drowsiness. ...
If the eyes are closed for a sufficiently long enough amount of the time, the motive force is in danger of falling asleep and Drowsiness signal processing detection module collects the EEG signals in real ...
doi:10.20319/mijst.2019.52.190201
fatcat:l66lix47rrflbgkuexxf2qbwye
Driver Drowsiness Detection Based on Face Feature and Perclos
2021
International Journal of Scientific Research in Science and Technology
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From the detected eye, iris regions for left and right eyes are used to calculate the PERCLOS measure (the percentage of total time that eye is closed). ...
The method attempts to recognize the face and then detecting the eye in every frame. ...
Driver Eye Detection This the second module with the help of this module to detect human eye through (haarcascade_frontalface_alt) this xml file. ...
doi:10.32628/ijsrst218319
fatcat:thaclnl74fcqnen7j4nlgblhji
A Survey on Driver Fatigue-Drowsiness Detection System
2016
International Journal Of Engineering And Computer Science
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We express our immense pleasure and thankfulness to all faculty members of the Department of Computer Science & Engineering of Sree Buddha College of Engineering, Alappuzha. ...
The approach starts with the detection of head-shoulders of the figure in the image, followed by face and eye detections and eye openness estimation. ...
The driver-drowsiness level is measured as PERCLOS, which is the percentage of eye closure time during a certain time interval. ...
doi:10.18535/ijecs/v5i11.92
fatcat:q34cj7cr6rcq7cn6tqrdqvyz4m
On-Road Drowsiness Alarm of Drivers using Raspberry Pi
2017
International Journal of Recent Trends in Engineering and Research
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In this paper, such a real-time video based vision processing system is proposed to estimate drowsiness of drivers and to alert them by a buzzer. Face is detected by a YCbCr color model based filter. ...
Vision processing in real-time applications is the emerging research area. The environment based processing of live-videos encourages the researchers for inventions of good life hacking products. ...
INTRODUCTION Image processing is now named as vision processing that process image in the form of signal, images or videos from real-time sources. ...
doi:10.23883/ijrter.2017.3512.cpeeb
fatcat:zla4ajx7vrcd7fv3xra26ykjxe
CIRCUMVENTING TRAFFIC COLLISION INFLUENCED BY DROWSY DRIVING THROUGH IOT TECHNOLOGY
2019
International Journal of Recent Trends in Engineering and Research
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System uses Eye Aspect Ratio (EAR) as input to detect the drowsy state of driver. Whereas the entire system is executed in Raspberry Pi3 it uses web camera to detect eye blink and drowsiness. ...
Digital image processing (DIP) is an effective application which playsss a decisive role in road accident caused by drowsy driving. ...
CONCLUSION The real time drowsiness detection system here to locate driver's eyes to monitor them for fatigue is capable of detecting the drowsiness in a rapid manner. ...
doi:10.23883/ijrter.2019.5027.sofqs
fatcat:3pkhpp2ztbbpjaswjhghvofhju
An automatic driver drowsiness alert system by using GSM
2017
2017 11th International Conference on Intelligent Systems and Control (ISCO)
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It is important for driving support systems to detect the status/activity of driver's consciousness. Detecting onset of driver fatigue could prevent the accidents caused by drowsy driving. ...
EEG signal is one of the most predictive and reliable measurements by the analysis of alpha, beta and theta band power etc, which are considered as direct factors associated with human drowsiness. ...
, in-vehicle, real-time drowsy using Lab VIEW tool and the drowsiness level is detected driver detection and fatigue alerting system.System that and the alarm signal will be activated by the alert system ...
doi:10.1109/isco.2017.7855966
fatcat:oz2g4mzysrgrnaewqlghzxh2me
Real-Time Driver Drowsiness Identification Based on Eye-State Analysis
2022
International Journal for Research in Applied Science and Engineering Technology
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Machine Learning has brought progression in video processing which enables images to be analysed with accuracy. Keywords: Drowsiness detection, OpenCV, Dlib, Driver Drowsiness, Eye-state analysis. ...
Abstract: Driving while being drowsy has become one of the major reasons of causing road accidents. ...
The focus will be placed on designing a system that will accurately monitor the open or closed state of the driver's eyes in real-time. ...
doi:10.22214/ijraset.2022.42853
fatcat:ulbjdir4drdhdcu47w7xuuw7iq
Real time Drowsy Driver Detection using Polynomial Kernel based Support Vector Machine
2021
International Journal for Research in Applied Science and Engineering Technology
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If any of the system automatically detects the driver's drowsiness and alert at real time may secure many lives. ...
There are various techniques through which drowsiness can be detected at real time but accuracy matters. ...
at real time for drowsiness detection. ...
doi:10.22214/ijraset.2021.38106
fatcat:eefnqy3lbvdeje2qqz3c4hphhe
Real-time Driver Drowsiness Detection with Android
2022
International Journal for Research in Applied Science and Engineering Technology
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In this detection approach, we developed an android app that utilizes image processing technology and analyse all the images captured through the user's phone camera. ...
This research paper presents a cost efficient approach to detect driver fatigue and monitor dizziness/drowsiness in real-time. ...
As we have initially developed this Real-time Driver Drowsiness Detection Android Application for the Android users to detect face and eyes closure. ...
doi:10.22214/ijraset.2022.42210
fatcat:fm4eieg6lfhzbk4fnla6km56fi
Driver Drowsiness Detection System
2022
International Journal for Research in Applied Science and Engineering Technology
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In this paper, we proposed a method for extracting detailed features of the eyes, the mouth, and positions of the head using OpenCV and Dlib library in order to estimate a driver's level of drowsiness. ...
Recent developments in video processing using machine learning have enabled images obtained from cameras to be analysed with high accuracy. ...
Kose1, Okan Kopuklu2 , Alexander Unnervik3 and Gerhard Rigoll4 18 Jul 2019 CNN Based Spatio-Temporal Approach They Detecting Driver Drowsiness in Real Time Through Deep Learning Based Object Detection ...
doi:10.22214/ijraset.2022.42109
fatcat:tczyrxfcsjfnbmnyvbwuqdoxui
Review on Drowsiness Detection
2018
EAI Endorsed Transactions on Smart Cities
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Also, the discovery of drowsiness with eyes open is conceivable. In countenance detection technology, driver weariness recognition is one of the major possible businesses uses. ...
Many technologies are used for detecting the weariness of the driver. It is a review paper of numerous advancements utilized by various scientists. In addition, human conduct can also be studied. ...
Real-Time Nonintrusive Monitoring and Detection of Eye Blinking in view of Accident Prevention due to Drowsiness In this paper, 18% of mishaps including drowsiness are the primary factor stated in review ...
doi:10.4108/eai.13-7-2018.165517
fatcat:pqo4mze4zrdb7h26n43z5chblu
Morphology based Facial Feature Extraction and Facial Expression Recognition for Driver Vigilance
2012
International Journal of Computer Applications
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Therefore, the use of assistive systems that monitor a driver's level of vigilance and alert the driver in case of drowsiness and distraction can be significant in the prevention of accidents. ...
The parameters used for detecting fatigue are: eye closure duration measured through eye state information, head movement through orientation of head ellipse and yawning analyzed through mouth state information ...
The driver-drowsiness level via eye status is measured through PERCLOS [14] , which is the percentage of eye closure time during a certain time interval. ...
doi:10.5120/8014-1142
fatcat:cqulv73uzzf6plscr4ussbzwbm
Real-Time Warning System for Driver Drowsiness Detection Using Visual Information
2009
Journal of Intelligent and Robotic Systems
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Examples of different images of drivers taken in a real vehicle are shown to validate the algorithm. ...
The aim of this system is to locate, to track and to analyze the face and the eyes to compute a drowsiness index, working under varying light conditions and in real time. ...
Acknowledgements This work was supported in part by the Spanish Government through the CICYT projects VISVIA (Grant TRA2007-67786-C02-02) and POCIMA (Grand TRA2007-67374-C02-01). ...
doi:10.1007/s10846-009-9391-1
fatcat:ipd3i4h6njfgdjxopm6tbi2qhq
Enhanced Image Processing and Fuzzy Logic Approach for Optimizing Driver Drowsiness Detection
2022
Applied Computational Intelligence and Soft Computing
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This study aims to design a nonintrusive real-time drowsiness system based on image processing and fuzzy logic techniques. ...
It extracted eye blink duration and mouth features to detect driver drowsiness based on the desired facial feature image in a specific driver video frame. ...
Online Data Analysis and Training for the Eye and the Mouth. In this section, the system focused on the analysis of real-time driver drowsiness detection. ...
doi:10.1155/2022/9551203
fatcat:k65e35x3yjc2bpg6lmyagewssa
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