Protection of regional object and camera tampering

Protection of regional object and camera tampering is very important in video surveillance and security applications. This paper presents a novel technique for protection of regional object and camera tampering detection. The monitoring regions are set artificially in the surveillance background scenes for protecting regional object, and cameras positions are also selected for camera tampering. According to the motion segmentation results based on background substraction model, alarm is triggered in comparison with the monitoring regions. The multiple original background images are sent into buffer and stored for protecting camera tampering. In order to recognize the slight shake of the camera, the normalized histogram distribution is utilized to detect the camera tampering. Experimental results show that the proposed algorithms can efficiently detect the abnormal events for protection of regional object and camera tampering.