In this paper, we propose the intelligent unmanned anti-theft system using network cameras. To do this, we use two Internet Protocol (IP) cameras, which are installed at the inside and the outside of the restricted area. First of all, the external camera is used to monitor a potential intruder entering the restricted area in real time. To detect the potential intruder from sequential images obtained by external IP camera, we propose the robust algorithm combining the background modeling, the hybrid silhouette, the convex summation, the morphology and the smoothing. Once the intruder is detected by the external camera, the internal camera with pan-tilt mechanism is then activated and starts tracking the intruder and monitoring the prescribed valuables registered with some feature points in the database. To track the intruder, we propose the tracking algorithm using the background elimination and the histogram. And then, we completes the proposed anti-theft system by using the Scale Invariant Feature Transform (SIFT) algorithm in order to monitor whether the intruder steals the prescribed valuables or not. Finally, we have shown the effectiveness and the applicability of the proposed method through experiments.
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