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Research Article Open Access
Now a day’s traffic jam is a major problem in daily life in urban areas. Increasing number of vehicles is causing more traffic jam day by day. One method to overcome the traffic problem is to develop an intelligent traffic detection system. So we are proposing “Traffic Density Measurement using image processing: An SVM approach” which is based on the measurement of traffic density on the road using camera and image processing techniques. A web camera will be placed in each road of the city that will capture the still images of the roads. After processing the input image, the density of vehicles will be measured and provide us information if any road is blocked by traffic. The main goal of this method is to detect if there is high traffic density or low so that we can choose alternative road to use. Through the image processing technique we can measure the no of vehicles and using Support Vector Machine (SVM) we analysed our result. We set a threshold value to compare between high and low traffic density
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Author(s): Hosne-Al-Walid, Nafisa Anjum, Ummenur Tubba, Lamia Akter, Zerin Asfad
Image analysis, dilation, erosion, noise reduction and SVM classifier., Advanced Numerical Algorithms,Agent-Based Middleware,Artificial Intelligence Pattern/Image Recognition.