Feature Extractor Analysis for Traffic Clearance in Emergency for Ambulance and Fire Engines

Abstract

As problem of urban traffic congestion spreads, there is a pressing need for the introduction of advanced technology and equipment to improve the state of the art of traffic control. Traffic problems nowadays are increasing because of the growing number of vehicles and the limited resource provided by current infrastructures. The simplest way of controlling a traffic light uses timer for each phase. We propose a system for controlling the traffic light by image processing. The system will detect vehicles through images instead of using electronic sensors embedded in the pavement. A camera will be installed near the traffic signal it will capture the image sequences. Setting image of Emergency vehicles as reference image, the captured images are sequentially matched using image matching. Whenever an ambulance enters into the range of camera then it captures image and compare with the reference image. If it matches with reference image then signal will be altered and cleared, so as give a clear way to pass the Ambulance. It helps to save the lives of human being by providing clear way in traffic. Here the ambulance or fire engine vehicle are detected using object detection machine learning technique, The python script is executed in laptop with image processing and uses the SIFT algorithms.