Real Time Traffic Assesment using Image Processing

2020 ◽  
Author(s):  
Pushpalata ◽  
M. Sasikala
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Real Time Traffic

scholarly journals Real Time Traffic Density Count using Image Processing

2017 ◽  
Vol 162 (10) ◽  
pp. 8-12 ◽  
Author(s):  
Alisha Janrao ◽  
Mudit Gupta ◽  
Divya Chandwani ◽  
U. A.
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Traffic Density ◽  
Real Time Traffic

scholarly journals Design and Development of Traffic Control System using Image Processing

2021 ◽  
Vol 9 (VI) ◽  
pp. 3247-3252
Author(s):  
G. Kalyan
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Red Light ◽  
Traffic Density ◽  
The Road ◽  
Real Time Traffic ◽  
On The Road

Traffic congestion is now a big issue. Although it seems to penetrate throughout the world, urban towns are the ones which are most effected. And it is expanding in nature that it is necessary to understand the density of roads in real time to better regulate signals and efficient management of transport. Various traffic congestions, such as limited capacity, unrestricted demand, huge Red Light waits might occur. While insufficient capacity and unlimited demand are somehow interconnected, their delay in lighting is difficult to encode and not traffic dependant. The necessity to simulate and optimise traffic controls therefore arises in order to better meet this growing demand. The traffic management of information, ramp metering, and updates in real-time has been frequently used in recent years for image processing and monitoring systems. An image processing can also be used for the traffic density estimation. This research describes the approach for the computation of real-time traffic density by image processing for using live picture feed from cameras. It focuses also on the algorithm for the transmission of traffic signals on the road according to the density of vehicles and therefore aims to reduce road congestion, which reduces the number of accidents.

scholarly journals Real Time Traffic Light Controller Using Image Processing

IJARCCE ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 93-97
Author(s):  
Karthikeyan* N ◽  
Praveen Kumar N ◽  
Priyanka R
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Traffic Light ◽  
Real Time Traffic

Vehicle Detection and Counting in Traffic Video Based on OpenCV

2013 ◽  
Vol 361-363 ◽  
pp. 2232-2235
Author(s):  
Wen Jun Wang ◽  
Meng Gao
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Moving Objects ◽  
Social Economy ◽  
Space Vehicle ◽  
Region Of Interest ◽  
Moving Vehicle ◽  
Real Time Traffic ◽  
Detection And Counting ◽  
Traffic Video

With the development of modern social economy, the number of vehicles in China is growing rapidly, so how to get real-time traffic parameters has a very important significance in using the limited road space, vehicle video detection method based on image processing develop rapidly. With the improvement of image processing technology and microprocessor performance, makes video-based traffic parameter detection using universal. This paper deals with the real-time traffic video, gets each frame, uses Gaussian filter denoising, marks the region of interest (ROI), apply background subtraction algorithm based on average method, get the binarization foreground image, set threshold to eliminate the moving objects whose area is too small, check the boundary of ROI to judge the moving vehicle and counting, get the results as parameters of the intelligent transportation.

scholarly journals IoT Based Traffic Control System using Image Processing

2021 ◽  
Vol 9 (VII) ◽  
pp. 317-321
Author(s):  
Mr. Sachin Tyagi
Keyword(s):  
Image Processing ◽  
Control System ◽  
Real Time ◽  
Traffic Control ◽  
Traffic Management ◽  
Raspberry Pi ◽  
Traffic System ◽  
Traffic Efficiency ◽  
Real Time Traffic ◽  
Traffic Control System

In the current scenario we can see that the traffic jam has become a serious problem in rapidly growing cities (As per their population) of India by which there is increase in air pollution, Fuel consumption as well as vehicular density. So there is a requirement to find a new way for traffic controlling traffic system which will be managed through real time IoT based traffic control system using image processing. This is a smart traffic management system that is designed to control real time traffic system which consist of components of Raspberry Pi, Pi camera. Raspberry pi is the key component which is used to control all performance multitasking. By using cameras, we monitor different lanes constantly. Image processing is used to examine detection and counting no. of vehicles in different lanes. It increases the traffic efficiency and clearance. The signal light will be decided as per the no. of vehicle count using image processing.

scholarly journals Real Time Traffic Density Count using Image Processing

2013 ◽  
Vol 83 (9) ◽  
pp. 16-19 ◽  
Author(s):  
Naeem Abbas ◽  
Muhammad Tayyab ◽  
M. Tahir Qadri
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Traffic Density ◽  
Real Time Traffic
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