Off-time swimming pool surveillance using thermal imaging system

Abstract

This paper introduces an effective intruder detection algorithm for an off-time swimming pool surveillance using thermal imaging system. Two sub-algorithms are developed for intruder detection outside and inside swimming pool regions during off-time. The algorithm can detect not only moving human in different directions, but also any water activity in the swimming pool caused by human intruder such as swimming, water-splashing and others. The dimension of human head shape is used for detecting human head while the difference of black colour pixel between successive thermal images is the criteria employed to detect any water activity due to humans. Experimental results show that the intruder detection algorithm achieved high accuracy of 95.58% for region outside swimming pool and 92.44% for region inside swimming pool.