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Reseach Article

An Improved Frame Difference Background Subtraction Technique for Enhancing Road Safety at Night

by Clement Alabi, James Ben Hayfron-Acquah
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 1
Year of Publication: 2021
Authors: Clement Alabi, James Ben Hayfron-Acquah
10.5120/ijca2021921280

Clement Alabi, James Ben Hayfron-Acquah . An Improved Frame Difference Background Subtraction Technique for Enhancing Road Safety at Night. International Journal of Computer Applications. 183, 1 ( May 2021), 38-45. DOI=10.5120/ijca2021921280

@article{ 10.5120/ijca2021921280,
author = { Clement Alabi, James Ben Hayfron-Acquah },
title = { An Improved Frame Difference Background Subtraction Technique for Enhancing Road Safety at Night },
journal = { International Journal of Computer Applications },
issue_date = { May 2021 },
volume = { 183 },
number = { 1 },
month = { May },
year = { 2021 },
issn = { 0975-8887 },
pages = { 38-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number1/31894-2021921280/ },
doi = { 10.5120/ijca2021921280 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:15:36.398654+05:30
%A Clement Alabi
%A James Ben Hayfron-Acquah
%T An Improved Frame Difference Background Subtraction Technique for Enhancing Road Safety at Night
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 1
%P 38-45
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Night vision technology allows for vision in darkness as though just as in broad daylight. To this effect, this research is carried out to see the possibility of using thermal-based night vision to curb road accidents that have become rampant on the roads and consequently reduce damage and the loss of life. Thermal sensors have a higher range than the average vehicle head and taillights, which use the visible light spectrum. This study proposes a concept where signals are received from a FLIR camera, the grayscale images are processed by an enhanced technique; the WBODY_DET () algorithm in the MATLAB environment. This algorithm identifies and highlights all hot objects by drawing colored boundaries around them. The algorithm is configurable and can highlight categories of objects in a scene. For instance, engines can be highlighted with different colors from living bodies like humans, cattle, sheep, goats, cats, dogs, etc. for easy recognition by drivers/observers for further response. The crux of this algorithm is an object detection technique that uses simple thresholding. The accuracy of this algorithm is enhanced by using morphological operators and the property of connectedness within the resulting binary image to remove false positives. This heat-based vision system is best suited for night driving since all moving objects emit some form of heat energy due to the work involved in the movement. Findings show that the proposed model is highly efficient since it is fast, has over a 90% detection accuracy and it allows for easy identification of danger on the roads at night from longer distances and under bad visibility levels. It is recommended that all vehicles should be upgraded with this technology so the roads will be safer. It is also recommended that long-range cameras should be used as the longer the range of the camera the longer the reaction times the system will provide drivers and prevent a collision.

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Index Terms

Computer Science
Information Sciences

Keywords

Forward Looking Infrared (FLIR) Matrix Laboratory (MATLAB) WBODY_DET() (White body detection for images). Background Subtraction Technique Enhanced Road Safety Improved Frame Difference