| Issue |
MATEC Web of Conferences
Volume 61, 2016
The International Seminar on Applied Physics, Optoelectronics and Photonics (APOP 2016)
|
|
|---|---|---|
| Article Number | 02007 | |
| Number of page(s) | 6 | |
| Section | Chapter 2 Electronic Technology and Electrical Engineering | |
| DOI | https://doi.org/10.1051/matecconf/20166102007 | |
| Published online | 28 June 2016 | |
A Narrative Approach to Detect the Vehicles using color, texture and edge based techniques
1
Dept of CSE, Dayanand Sagar College of Engineering, Bangalore, India
2
Professor, Dept of CSE, Dayanand Sagar College of Engineering, Bangalore, India
a Corresponding author: Ravi Gaurav, gaurav.ravi9@gmail.com
Vehicle recognition is the chief stride in observing the speeding vehicles in a thruway. The feature arrangements caught by a stationary camera demonstrate to us that there’s a requirement for a vehicle location calculation which handles sudden light change furthermore the situations where the closer view converges away from plain sight. This paper gives us a study of different foundation subtraction systems that are utilized for recognizing the vehicles effectively. Vehicles proceeding onward street are of significance on the grounds that issues like movement blockage, monetary waste, sticking on the underpasses and over-extensions (if the vehicle going through is not of the passable size) are connected with them. Index Terms—Vehicle Detection, video sequences, foreground, background, MATLAB, RGB conversion.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.