LAUSR

Along with the development of information and communication technology, the world urban people now recognize a new term called Smart City. One of Smart City components is smart transportation, known as Intelligent Transportation System (ITS) in which there is transportation management on the highway. Installation of CCTV (Closed Circuit Television) on the streets are now widely performed. It can be used to monitor conditions and detect problems such as traffic jam and vehicle speed limit violation. This research focuses on vehicle speed estimation using image processing from video data and Euclidean distance method with many different camera angles. The first step, video data is extracted into frames and applied preprocessing to extracted frames to minimize shadow effect. Then, using Gaussian Mixture Model (GMM) to extract foreground image. In the next step, the obtained foreground is filtered using median filter, shadow removing, and morphology operation. The detected vehicle object will be tracked to determine the location in each frame to estimate the speed based on its distance between frames. From the obtained results, this system is capable on estimating the speed of moving vehicle with the lowest accuracy is 87.01% and the highest accuracy is 99.38%.