INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
This proposed system is used for Driver & Road safety system. Based on computer vision techniques , the driver’s face is located from a color video captured in a car. Then, face detection is employed to locate the regions of the driver’s eyes, which are used as the templates for eye tracking in subsequent frames. The tracked eye’s images are used for drowsiness detection in order to generate warning alarms. The proposed approach has three phases: Face, Eye detection and drowsiness detection. The role of image processing is to recognize the face of the driver and then extracts the image of the eyes of the driver for detection of drowsiness. The Haar face detection algorithm takes captured frames of image as input and then the detected face as output. It can be concluded this approach is a low cost and effective solution to reduce the number of accidents due to driver's Drowsiness to increase the transportation safety.
Keywords:
Raspberry pi, Eye tracking, Driver.
Cite Article:
"Driver Drowsiness Detection system using Raspberry pi", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 3, page no.214 - 218, March-2019, Available :http://www.ijsdr.org/papers/IJSDR1903037.pdf
Downloads:
000337071
Publication Details:
Published Paper ID: IJSDR1903037
Registration ID:190204
Published In: Volume 4 Issue 3, March-2019
DOI (Digital Object Identifier):
Page No: 214 - 218
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
Facebook Twitter Instagram LinkedIn