Driver Drowsiness Detection system using Raspberry pi
Dr.S.Priyadarsini
, Chahak Agarwal.D , Deshiya Narayan.M
Raspberry pi, Eye tracking, Driver.
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.
"Driver Drowsiness Detection system using Raspberry pi", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.4, Issue 3, page no.214 - 218, March-2019, Available :https://ijsdr.org/papers/IJSDR1903037.pdf
Volume 4
Issue 3,
March-2019
Pages : 214 - 218
Paper Reg. ID: IJSDR_190204
Published Paper Id: IJSDR1903037
Downloads: 000347250
Research Area: Engineering
Country: Virudhunagar, TamilNadu, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
