Survey on Camera Tampering Detection in Real Time Using Two Stage Scene Matching

Abstract

This survey describes a novel technique for camera tampering detection. It is implemented in real-time and was developed for use in surveillance and security applications. Cameras installed in many places are exposed to sabotage or tampering. The algorithm is based on background modelling, histograms comparison, edges comparison and analysis of the image’s average brightness.

 In the first stage, we use the intensity of edges as the main cue to detect the camera tampering events. Instead of using the entire edge points of the images, we sample the most significant edge points to represent the scene. Whenever the first stage detects the tampering event, the second stage is triggered to reduce false alarms. In the second stage, we propose an illumination change detector which can check the consistency of the scene structure using cell-based matching method. The experimental results demonstrate that our system can detect the camera tampering precisely and minimize false alarm even when the illumination changes dramatically or large crowds passing through the scene. The performance of this method is

shown to be extremely favorable in real-world settings.