| Issue |
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
|
|
|---|---|---|
| Article Number | 01055 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/e3sconf/202343001055 | |
| Published online | 06 October 2023 | |
Automated Weapon Detection System in CCTV’s Through Image Processing
1 Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Nizampet Road, Bachupally, Kukatpally, Hyderabad – 500090, Telangana State, India.
2 Uttaranchal School of Computing Sciences, Uttaranchal University, Dehradun, 248007, India
* Corresponding author: siri1686@grietcollege.com
In our study, we aim to detect various weapons through image processing using a combination of traditional machine learning algorithms and deep learning techniques. This would prove beneficial in anticipating unusual occurrences. The utilization of Closed-Circuit Televisions (CCTVs) has become widespread in the security and surveillance industry; however, it requires constant human monitoring to extract useful information, which is both tedious and prone to errors. The base paper deals with identifying only firearms. We intend to utilize machine learning and deep learning methods to recognize different weapons automatically, not only firearms and alert the CCTV monitor to that specific area.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.