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Reseach Article

Shortest Path Approach for Detection of Optimal Traffic Route

by Tejaswi K. Hude, S. S. Sambare
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 133 - Number 5
Year of Publication: 2016
Authors: Tejaswi K. Hude, S. S. Sambare
10.5120/ijca2016907848

Tejaswi K. Hude, S. S. Sambare . Shortest Path Approach for Detection of Optimal Traffic Route. International Journal of Computer Applications. 133, 5 ( January 2016), 10-13. DOI=10.5120/ijca2016907848

@article{ 10.5120/ijca2016907848,
author = { Tejaswi K. Hude, S. S. Sambare },
title = { Shortest Path Approach for Detection of Optimal Traffic Route },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 133 },
number = { 5 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 10-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume133/number5/23781-2016907848/ },
doi = { 10.5120/ijca2016907848 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:30:19.173355+05:30
%A Tejaswi K. Hude
%A S. S. Sambare
%T Shortest Path Approach for Detection of Optimal Traffic Route
%J International Journal of Computer Applications
%@ 0975-8887
%V 133
%N 5
%P 10-13
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents system which determines optimal traffic route with shortest path approach. Client request for optimal traffic route from given source to destination, server sends response with image processing. Proposed system uses Dijkstra’s algorithm to find optimal traffic route as shortest cost path. Every node is considered as place in the route from given source to destination. Cost of the path between two node is vehicle count. According to cost of the nodes system suggest optimal traffic route from given source to destination. For detecting vehicle density ,different image processing techniques and algorithms are used, like as background subtraction, image filtering, image binary and segmentation. System process on pre-recorded video stream at server side and suggest optimal traffic route. Paper also focuses on New Inter frame Difference algorithm for image processing for vehicle density detection.

References
  1. Shibam Das,Ambika Aery-A review:Shadow detection and shadow removal from images.-International Journal of eng trends and technology(IJETT)-vol 4,may 2013.
  2. Nilesh J. Uke and Ravindra c.Thool-Moving Vehicle Detection for measuring traffic count using opencv-2013.
  3. Norbert Buch,James Orwell-A Review of computer vision techniques for the analysis of urban traffic.-IEEE Transaction on intelligent transportation system,vol 12,sept 2011.
  4. Pejman Niksaz-Automatic traffic estimation using image processing-International journal of signal processing,image processing and pattern recognition,vol 5,dec 2012.
  5. Wenxuan Shi and Jie Li-EURASIP Journal on Advances in signal processing –a Springeropen Journal 2012.
  6. Nobuyuki Otsu-A Threshold selection method from gray-level histograms-IEEE,transaction on systems,Man and cybernetics,vol no 1,jan 1979.
  7. Shortest path algorithms:An Evaluation using real road networks-article in transportation science:feb 1998-Source-DBLP.
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive Background Generation Morphological Filtering Virtual Detector.