DocumentCode :
237886
Title :
Safe driving by detecting lane discipline and driver drowsiness
Author :
Katyal, Yashika ; Alur, Suhas ; Dwivedi, Shipra
Author_Institution :
Vellore Inst. of Technol., Electron. & Commun. Eng., Chennai, India
fYear :
2014
fDate :
8-10 May 2014
Firstpage :
1008
Lastpage :
1012
Abstract :
In the modern day world, road accidents have become very common. They not only cause damage to property, but also keep at risk the lives of people travelling. Road safety is an issue of national concern, looking at its magnitude and the incidental negative impacts on the economy, public health, safety and the general welfare of the people. These road accidents may be due to many reasons like rash driving, drink and driving, inexperience, jumping signals, ignoring signboards. Since, road accidents is an important issue to be addressed, this paper will be concentrating on avoiding the road accidents by concentrating mainly on-Drunk driving or drowsiness and lane discipline. The paper has two parts. Firstly, lane detection using Hough Transform. Secondly, eye detection of driver for drowsiness detection. Thus, the main focus is on the fatigue of the driver and his maintenance of lane discipline.
Keywords :
Hough transforms; driver information systems; gaze tracking; object detection; road accidents; road safety; Hough transform; drink and driving; driver drowsiness; driver fatigue; drowsiness detection; eye detection; general welfare; incidental negative impacts; jumping signals; lane detection; lane discipline detection; national concern; public health; public safety; rash driving; road accidents; road safety; safe driving; signboard ignorance; travelling people; Accidents; Cameras; Face; Image edge detection; Image segmentation; Robots; Robustness; Driver Drowsiness; Eye Detection; Hough Transform; Lane Detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
Conference_Location :
Ramanathapuram
Print_ISBN :
978-1-4799-3913-8
Type :
conf
DOI :
10.1109/ICACCCT.2014.7019248
Filename :
7019248
Link To Document :
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