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Application of Image Processing and Data Mining Techniques for Traffic Density Estimation and Prediction

Mirzanur Rahman1 , Surojit Dey2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 248-253, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.248253

Online published on Mar 31, 2019

Copyright © Mirzanur Rahman, Surojit Dey . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Mirzanur Rahman, Surojit Dey, “Application of Image Processing and Data Mining Techniques for Traffic Density Estimation and Prediction,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.248-253, 2019.

MLA Style Citation: Mirzanur Rahman, Surojit Dey "Application of Image Processing and Data Mining Techniques for Traffic Density Estimation and Prediction." International Journal of Computer Sciences and Engineering 7.3 (2019): 248-253.

APA Style Citation: Mirzanur Rahman, Surojit Dey, (2019). Application of Image Processing and Data Mining Techniques for Traffic Density Estimation and Prediction. International Journal of Computer Sciences and Engineering, 7(3), 248-253.

BibTex Style Citation:
@article{Rahman_2019,
author = {Mirzanur Rahman, Surojit Dey},
title = {Application of Image Processing and Data Mining Techniques for Traffic Density Estimation and Prediction},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {248-253},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3825},
doi = {https://doi.org/10.26438/ijcse/v7i3.248253}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.248253}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3825
TI - Application of Image Processing and Data Mining Techniques for Traffic Density Estimation and Prediction
T2 - International Journal of Computer Sciences and Engineering
AU - Mirzanur Rahman, Surojit Dey
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 248-253
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

Most of the common problems encounter by the today’s world is traffic congestion. As populations as well as number of vehicles are increasing in the cities and towns, traffic congestion has become a major problem for the time being. Delays, fuel consumption and air pollutions are some of the problems arise from traffic congestion. There are many reasons for traffic congestion like narrow roads, lack of alternate route, slow traffic speed, improper uses of traffic signals etc. In this paper, we proposed a system to overcome some these problems by providing an alternate route for the vehicles by predicting a possible congestion ahead of that road.

Key-Words / Index Term

Traffic congestion, Traffic density, vehicle count, vehicle speed, background subtraction, frame, Artificial neural network (ANN), Epoch

References

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