Welcome to IJSDR UGC CARE norms ugc approved journal norms IJRTI Research Journal | ISSN : 2455-2631
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.15 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Issue: June 2023

Volume 8 | Issue 6

Impact factor: 8.15

Click Here For more Info

Imp Links for Author
Imp Links for Reviewer
Research Area
Subscribe IJSDR
Visitor Counter

Copyright Infringement Claims
Indexing Partner
Published Paper Details
Paper Title: Drowsiness Detecting from Face Images (eyes and mouth) Using Tensorflow & Open-cv with Real time Video
Authors Name: Dipesh Patel , Kunal Bendale , Kalpesh Patil , Shubham Patil , Prof. Mahendra Jagtap
Unique Id: IJSDR2204034
Published In: Volume 7 Issue 4, May-2022
Abstract: In recent years, drowsiness is the main cause of the accidents in India due to lack of sleep, tiredness and so on. In order to reduce the case of vehicle accidents caused by drowsiness of the driver is to detect them and warn them using an alarm. Many techniques, such as eye retina detection, have been used to detect sleepiness by facial features. Here in this paper, we propose a method for detecting the driver’s drowsiness by detecting the person’s closed eye for a few seconds. In this report, we propose a more accurate method for detecting drowsiness, by. The main contribution for this project is the drowsiness detection and warning, which is based on the person’s open or closed eye. This project discuss on how to detect the eyes of the driver from the real time environment using the webcam represents the dashboard camera in a car. By using the real time detection, author use the built-in laptop webcam to detect the eyes of the demonstrator. The drowsiness detection ystem will detect the open and closed eye. The designed system will detect the face area and the coordinate of the eye. Detecting the face area is narrow down to detect eyes within face area. Both left and right eyes will be framed out once it found. The parameters of the eyes the eyes will be captured, whether it is closed or open. If the eyes are found closed for 4 consecutive frames, it is confirm that the driver is in drowsiness condition.
Keywords: Open CV, Tensor Flow, Detection, Drowsiness System, Machine Learning system
Cite Article: "Drowsiness Detecting from Face Images (eyes and mouth) Using Tensorflow & Open-cv with Real time Video", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 4, page no.190 - 193, May-2022, Available :http://www.ijsdr.org/papers/IJSDR2204034.pdf
Downloads: 000223214
Publication Details: Published Paper ID: IJSDR2204034
Registration ID:200306
Published In: Volume 7 Issue 4, May-2022
DOI (Digital Object Identifier):
Page No: 190 - 193
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

Click Here to Download This Article

Article Preview

Click here for Article Preview

Major Indexing from www.ijsdr.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

Track Paper
Important Links
Conference Proposal
DOI (A digital object identifier)

Providing A digital object identifier by DOI
How to GET DOI and Hard Copy Related
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Creative Commons License
This material is Open Knowledge
This material is Open Data
This material is Open Content
Social Media

Indexing Partner