This paper is published in Volume-5, Issue-1, 2019
Area
Computer Science
Author
Greeshma C. A., Nidhindas K. R., Parvathi Kishore P., Sreejith P. S.
Org/Univ
Universal Engineering College, Mathilakam, Kerala, India
Pub. Date
19 February, 2019
Paper ID
V5I1-1338
Publisher
Keywords
Computer vision, Traffic density, Arduino uno, Open CV

Citationsacebook

IEEE
Greeshma C. A., Nidhindas K. R., Parvathi Kishore P., Sreejith P. S.. Traffic control using computer vision, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Greeshma C. A., Nidhindas K. R., Parvathi Kishore P., Sreejith P. S. (2019). Traffic control using computer vision. International Journal of Advance Research, Ideas and Innovations in Technology, 5(1) www.IJARIIT.com.

MLA
Greeshma C. A., Nidhindas K. R., Parvathi Kishore P., Sreejith P. S.. "Traffic control using computer vision." International Journal of Advance Research, Ideas and Innovations in Technology 5.1 (2019). www.IJARIIT.com.

Abstract

Now a days traffic density on the streets increasing around the world tremendously . It causes several problems on the day to day life of people. As we know that it is the era of speed, so that nobody wants to wait for a long time at any cost. Everybody prefers to low traffic density streets. This proposed system introduced a vehicle density-based traffic control system to avoid above issues. This problem can be resolved by controlling the traffic density on the roads. This system introduces a new method to control vehicle density by controlling the traffic lights using Image processing. Vehicle density is measured using predefined classifiers available in image processing. If the measured density is above the normal density (threshold value) it passes an indication to the microcontroller which controls the projector and thereby we can give appropriate traffic signal to display.