Detection of Normal and Abnormal Conditions for Boundary Surveillance using Unmanned Aerial Vehicle

There are several advanced methods to detect objects, humans, etc., which requires large dataset for training. In this paper, a difference of difference (DoD) technique has been proposed to detect normal and abnormal conditions with minimal dataset during surveillance. This dataset has been used for setting a threshold value to detect condition without training. Captured images have been compared with created dataset toget net difference value and this value has been compared with the threshold value to detect normal and abnormal conditions. This technique can be used at no-man zone areas, boundaries and security borders, and also it can be used as a front-liner along with any advanced technique for surveillance application. This method has been simulated on real images using MATLAB and conducted practical experiment using quad rotor, RPi and ROS.