Automated Detection of Firearms and Knives in a CCTV Image

Sensors

Michał Grega¹  Andrzej Matiolański²  Piotr Guzik²  Mikoᐪj Leszczuk² 

[1] AGH University of Science and Technology, al. Mickiewicza 30, Krakow 30-059, Poland

关键词: Haar cascade;    OpenCV;    pattern recognition;    fuzzy classifier;    data analysis;    feature descriptor;    knife detection;    firearm detection;   

DOI  :  10.3390/s16010047

来源: mdpi

【 摘 要 】

Closed circuit television systems (CCTV) are becoming more and more popular and are being deployed in many offices, housing estates and in most public spaces. Monitoring systems have been implemented in many European and American 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 human factors. In this paper, we 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 or knife is visible in the image. We have focused on limiting the number of false alarms in order to allow for a real-life application of the system. The specificity and sensitivity of the knife detection are significantly better than others published recently. We have also managed to propose a version of a firearm detection algorithm that offers a near-zero rate of false alarms. We have shown that it is possible to create a system that is 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.

【 授权许可】

CC BY   
© 2016 by the authors; licensee MDPI, Basel, Switzerland.