NDLI: Survey on various lane and driver detection techniques based on image processing for hilly terrain

Content Provider	IET Digital Library
Author	Manoharan, Kodeeswari Daniel, Philemon
Abstract	As vehicular traffic continues to grow traffic management and prevention of accidents has become a major concern. This problem only gets magnified when travel on the mountainous roads are considered. This study is especially focused toward Himalayan mountains as they pose a greater risk because of their rugged natural setting. This study investigates crucial problems faced on the hilly roads and the challenges in translating existing driver-assistance systems to such roads. The survey probes every lane detection algorithms, image processing techniques and various assistance features for applicability to hilly roads discussing the pros and cons for each of them. Conclusions are drawn as to deduce the more suitable methods that can be improvised and re-tuned to adapt them for mountainous roads.
Starting Page	1511
Ending Page	1520
Page Count	10
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 9, Sep (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0864
Journal	IET Image Processing
Publisher Date	2018-04-10
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Assistance Features Computer Vision And Image Processing Technique Crucial Problem Driver Detection Technique Driver Information System Existing Driver-assistance System Greater Risk Hilly Roads Hilly Terrain Himalayan Mountains Image Processing Technique Mountainous Roads Optical, Image And Video Signal Processing Road Safety Road Traffic Road Vehicle Roads Rugged Natural Setting Survey Probes Every Lane Detection Algorithm Traffic Engineering Computing Traffic Management Travel Vehicular Traffic
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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