Closed circuit television systems (CCTV) are becoming more popular and are being deployed in many offices, housing estates and in the most public spaces. Monitoring systems have been implemented in many foreign cities. This makes for an enormous load for the CCTV operators, as the number of camera views a single operator can monitor is limited by the human factors. The projects focus on the task of automated detection and recognition of dangerous situations for CCTV systems. We propose algorithms that are able to alert the human operator when a firearm is visible in the image and also have focussed on limiting the number of false alarms, in order to allow a real life application of the system. Managed to propose a version of a firearm detection algorithm that offers a near zero rate of false alarms and have shown that it is possible to create a system that are capable of an early warning in a dangerous situation, which may lead to faster and more effective response times and a reduction in the number of potential victims.