Page 81 - Kỷ yếu hội thảo khoa học lần thứ 12 - Công nghệ thông tin và Ứng dụng trong các lĩnh vực (CITA 2023)

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Weapon Detection with YOLO Model Version 5, 7, 8

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Doan Trung Son and Nguyen Thi Khanh Tram , Vo Thai Anh
1 Phenikaa University, Ha Noi, Vietnam
2 University of Engineering and Technology, VietNam National University
3 Can Tho University, Can Tho, Vietnam
son.doantrung@phenikaa-uni.edu.vn

Abstract. Today, the crime rate due to the use of hot weapons is very high, early
detection of possible violent situations is extremely important for security.
One way to prevent these situations is by detecting the presence of dangerous
objects in surveillance video. Current surveillance systems still require human
supervision, are low-precision and costly. AI (Artificial Intelligence) technology
is being used in almost all sectors of society. Recently, the Smart Camera
application that uses Artificial Intelligence to solve complex problems is
increasingly popular. This paper focuses on improving the performance of
Surveillance Cameras to detect pistol in both accuracy and diversity by using
YOLO -V5, V7, V8 models.

Keywords: Hot Weapon, Pistol Detection, YOLO-V5, YOLO-V7, YOLO-V8.

1 Introduction

According to statistics, criminals use hot weapons to commit crimes such as fights,
riots, terrorism, drug trafficking etc. in social life, in which the risk of security and
safety for people is the most important issue today in social security. Recently, there
have been consecutive cases related to "hot" weapons, making people really worried
and insecure. From the above situation, it is more urgent than ever to tighten arms
management and especially introduce early warning measures for people to prevent
them. Automatic image recognition is becoming popular and applied in many fields
[10] including detecting dangerous situations based on surveillance camera recordings.
This article deals with the analysis of footage from video obtained by surveillance
camera systems. Some typical Smart Camera systems include: IBM Camera
Surveillance System [8] which automatically tracks and detects moving objects in a
surveillance area, KNIGHT System [9] which specifically allows subject tracking from
multiple surveillance cameras. However, the cost of these solutions is quite high or does
not support the implementation of many specific problems in Vietnam.

Related Research. In [1] Olmos proposes A binocular image fusion approach for
minimizing false positives in handpistol detection with deep learning. Object detection
models have known important improvements in the recent years. The state-of-the art

ISBN: 978-604-80-8083-9 CITA 2023