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Article . 2018
License: CC BY
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Article . 2018
License: CC BY
Data sources: Datacite
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Prevention Of Road Accidents Using Image Processing On Video Streams: A Review

Authors: Swati S. Patil1, Amit S.Kakad2 & Dr C. M. Jadhao3;

Prevention Of Road Accidents Using Image Processing On Video Streams: A Review

Abstract

In this review paper we are simply going to review some research papers related to the prevention of road accidents using image processing. Generally road accidents happens due the fact that over speeding of vehicles or not wearing helmet or drunken drive. All these necessary safety parameters should be considered which can reduce the road accidents and may save a life. By studying all these papers we will came to know that the systems which are already implemented are using varioustechniques. Like for estimation of speed of vehicle Doppler effect is used. Also an analog to digital conversion is done which is used to determine the speed of vehicle and the license plate extraction which is used to extract the license plate and email it to Toll.For feature extraction of images some algorithms were used as descriptors i.e. SURF, HAAR, HOG and LBP. For image classification some Function Networks were used as classifiers i.e. Multilayer Perceptron, Support Vector Machines and Radial-Bases Function Networks. For fall detection background subtraction and optical character recognition methods is used whereas for helmet detection background subtraction and Hough transform descriptor is used.

Keywords

road accidents, MATLAB, video stream, speed detection, helmet detection.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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