• Priyanka Pote
• Jyotsna Gosavi
• Shubham Padwankar
• Poonam Salunke
• Divya Sharma

Today’s traffic management system uses pre-set timers for traffic lights to control traffic congestion, which is an open loop system that leads to an unreliable traffic management. This problem can be solved by using closed loop system in which we capture image of current traffic scenario and digitally process the captured image to count number of vehicles detected in each lane using image processing techniques based on object detection in MATLAB software. Therefore priority to lanes and timers for traffic lights will get set according to the density of traffic present in respective lanes. Vehicle detection and count is carried out using blob detection technique that uses the Blob Analysis block to calculate statistics for labeled regions in a binary image. Additionally, this system includes an application of ambulance detection. Ambulance detection is done using color thresholding technique by using the selected threshold value of siren of ambulance and priority will be given to that lane in which ambulance is detected irrespective of the traffic density.

Close loop system, Vehicle detection, MATLAB, Blob detection, Color thresholding

"Vehicle Detection and Count using Image Processing in Smart Traffic Management System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 4, page no.146-150, April-2018, Available :http://www.jetir.org/papers/JETIR1804030.pdf

"Vehicle Detection and Count using Image Processing in Smart Traffic Management System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 4, page no. pp146-150, April-2018, Available at : http://www.jetir.org/papers/JETIR1804030.pdf