CCTV Surveillance for Unprecedented Violence and Traffic Monitoring

Abstract

Monitoring of traffic and unprecedented violence has become very much necessary in the urban as well as the rural areas, so the paper attempts to develop a CCTV surveillance for unprecedented violence and traffic monitoring. The proffered method performs the synchronization of the videos and does proper alliance employing the algorithms of motion detection and contour filtering. The steps in motion detection identifies the movement of the objects such as vehicles and unprecedented activities whereas the filtering is used to identify the object itself using its color. The synchronization and the alignment process affords to provide the details of the each objects on the scenario. The proposed algorithm is developed in Java which assists its model using its library that is open source. The validation of the proposed model was carried out using the data set acquired from real time and results were acquired. Moreover the results acquired were compared with the algorithms that were created in the early stages, the comparison proved that the proffered model was capable of obtaining a consecutive quick outcomes of 12.3912 *factor than the existing methods for the resolution of the video used in testing was 240.01x 320.01 with 40 frames per second with cameras of high definition. Further the results acquired were computed to run the application of the embedded CPU and the GPU processors.