Manuscript Number : IJSRST1841352

Review on Traffic Density Estimation Using Computer Vision Technique

Authors(2) :-Sonali D. Choudhari, Dr. V. T. Gaikwad

The activity on the streets is builds step by step. The need of creating framework that can oversee and control the movement on street . The movement of numerous vehicle on streets is additionally critical for taking different choices identified with activity. The framework brings an activity picture from a CCTV camera to process in the framework as an information. From that point onward, the framework finds for movement clog and gets the outcomes in three rush hour gridlock conditions as Flow, Heavy, and Jammed. At long last, a client can utilize the framework for a transportation arranging or a convergence movement control. For execution, the framework utilizes a picture preparing system to dissect for a movement condition. It recognizes what number of items or autos out and about. And after that, the framework associates a movement condition result with a database for a transportation arranging.

Authors and Affiliations

Sonali D. Choudhari
M.E Scholar, Department of Electronics & Telecommunication Engineering, Sipna College of Engineering and Technology, Amravati, Maharashtra, India
Dr. V. T. Gaikwad
Professor, Department of Information Technology, Sipna College of Engineering and Technology, Amravati, Maharashtra, India

Image Processing, Image Segmentation, CCTV camera, Traffic Density Estimation

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Publication Details

Published in : Volume 4 | Issue 2 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 1496-1500
Manuscript Number : IJSRST1841352
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Sonali D. Choudhari, Dr. V. T. Gaikwad, " Review on Traffic Density Estimation Using Computer Vision Technique", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 4, Issue 2, pp.1496-1500, January-February-2018.
Journal URL : https://ijsrst.com/IJSRST1841352
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