Density Based Emergency Vehicle Detection and Traffic Signal Controlling using Image Processing
Sriharsha Vikruthi1, E.V.N.Jyothi2, Pallam Reddy Venkata Subba Reddy3
1Sriharsha Vikruthi, Assistant Professor,Cse Department, Pace Institute Of Technology & Sciences, Ongole, Ap, India.
2E.V.N.Jyothi, Associate Professor, Cse Department,Pace Institute Of Technology & Sciences, Ongole, Ap, India.
3Pallamreddy Venkatasubbareddy, Associate Professor, Cse Department, Pace Institute Of Technology & Sciences, Ongole, Ap, India.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 3994-3998 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6139018520/2020©BEIESP | DOI: 10.35940/ijrte.E6139.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In present day generation, the number of vehicles is increased because of increase in population. Hence in this paper, the design of vehicle detection and traffic control signal is implemented by using processing of image. The proposed system main intent is to acquire the images for the vehicle and control the traffic signal. Firstly an image is captures from the web camera, which is placed in traffic control area on the road. After this the traffic density is calculated from the obtained images. Basically, this image enhancement performs its operation in two forms they are operating phase and learning phase. Here the captured image as enhanced by using the image enhancement method. Hence the main advantage of this proposes system is that it processes the entire operation in simple way with high speed. The proposed system will capture the images of road areas in effective way. Hence the propose system has various features which will determine the color, width and many other. The proposed implemented system is mat lab software to prevent congestion of heavy traffic.
Keywords: Road Detection; Image Enhancement; Thresholding; Flow Estimation; Feature Selection; Traffic Density, Traffic Congestion.
Scope of the Article: Signal and Speech Processing.