An intelligent vision system for monitoring security and surveillance of ATM

This paper presents an automated system to increase the security and surveillance of ATM kiosks. Due to the increase of robbery in ATM kiosks, it is important to employ an automated surveillance system to protect and secure the ATM machine from threats. Currently, a camera attached with the ATM unit, records and transmits the video feed to the main server of the bank. Around the clock, this manual surveillance utilizes a lot of bandwidth for transmission. There is waste of memory and late response to emergency situation. Consequently, early detection of the situation is necessary to take preventive measures against an ongoing burglary. In this paper it is possible to detect whether a person is wearing a mask or not. The proposed system is also capable of counting the number of people present inside the ATM kiosk and generate a warning signal, thereby removes a constant human supervision, reducing the storage of unnecessary video feed and transmitting only an anomalous situation, a faster response to a threat by shutting down the ATM machine as soon the system detects the threat.