Abstract
Today theft and crimes rates are very high, so there is a significant need to monitor and monitor our property. Cameras usage was limited to surveillance; nowadays we don’t, merely, need to monitor our offices, banks and houses; but we also need to lessen and /or prevent damages; including as theft, and other types of crimes. Cameras can track pedestrians, monitor traffic and city management, etc. These cameras send the video frames in real time to our system; the latter detects the moving objects within the frame, to decide whether the moving object is a human or not. The research aims to identify the requirements to develop an Anti-theft Camera real-time recorder for personal property surveillance, in addition to try and evaluate the proposed Anti-theft Camera real-time recorder system. Our goal is to discover and analyze the pedestrian (movement), whatever the lighting or camera angle , by analyzing the video then restart an alarm to prevent the thieves all in real time, even though if there are some factors of disruption .In this research we have developed a system to detect a moving objects within the video frame depend on developing subtracting the current image coming from the video frame from the stored reference image (or the previous image coming from the video frame); it is called blocks detection. To lessen to complexity to become more effective in real time We have got relative highly precise results; (after conducting a trial over 50 moving objects within the image). The results approximate the 50 actually detected moving objects in the video. This has been achieved through improving and analyzing images taken from the video frame. We got a high accuracy results relatively, through applying multiple algorithms to detect motion within video frame.
Published Version
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