Adaptive Background Generation Method for Automated Teller Machine (ATM) with an Integrated Video Monitoring System

Efficiency of most conventional background subtraction systems used in video surveillance systems depends on the correct choice of a threshold. To prevent this dependency, a new adaptive background modeling method, is proposed in this paper for ATM video monitoring systems, based on the frame averaging method and threshold values. The proposed output of the algorithm was tested on the created ATM data set. The findings of the new approach were compared to those of the traditional Gaussian mixture model. The increased detection efficiency is due to the adaptive threshold introduced in the current background pixel determination process