Weapons Detection of Criminal Activities Based on Computer Vision

Sakib-Ahmod; Shoyaib Mahmud; Shammir Hossain; Yeasin Arafat; Jakia Rawnak Jahan; Ohidujjaman; Raihana Zannat

doi:doi:10.11648/j.advances.20210204.11

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Weapons Detection of Criminal Activities Based on Computer Vision

Sakib-Ahmod, Shoyaib Mahmud, Shammir Hossain, Yeasin Arafat, Jakia Rawnak Jahan, Ohidujjaman, Raihana Zannat

Published in Advances (Volume 2, Issue 4)

Received: 23 October 2021 Accepted: 9 November 2021 Published: 17 November 2021

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Abstract

In contemporary the term 'computer vision' is applicable vastly for significant research arena. Many researchers have a keen interest in this field. In this computer vision-based system, there have managed to detect weapons of two types (different guns and knives) to inform the concerned authority of property about crimes ongoing inside the place. While a property is under such criminal activity that the criminals carry guns or/and knives with them, the system detects those weapons through a camera integrated module and runs the necessary functions accordingly. Due to witnessing weapons, the system immediately informs the concerned authority to alert them about the upcoming risk to the property via mobile message and call. Consequently, the proprietor is alerted about the forthcoming risk and takes possible measures to handle the situation. Apart from that, the system can make sound alarms around the place of crime so that the people near to the property can come forward to help. This research is applicable in various properties such as banks, offices, homes or anywhere to protect the valuable properties from being theft or robbed. In this research computer vision and machine learning approaches are applied for the optimal result prediction.

Published in	Advances (Volume 2, Issue 4)
DOI	10.11648/j.advances.20210204.11
Page(s)	64-67
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Computer Vision, Image Processing, Machine Learning, Artificial Intelligence, Weapon Detection

References

[1]	Rohit Kumar Tiwari and Gyanendra K. Verma, "A Computer Vision-based Framework for Visual Gun Detection Using Harris Interest Point Detector," Procedia Computer Science Volume 54, 2015, Pages 703-712.
[2]	H. Jain and et al., "Weapon Detection using Artificial Intelligence and Deep Learning for Security Applications," 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC), Coimbatore, India, 2020, pp. 193-198.
[3]	Glowacz, A. and et al., "Visual detection of knives in security applications using Active Appearance Models." Multimedia Tools and Applications, 2013, 74 (12), 4253–4267.
[4]	Suraj Satpute and et al., "Real Time Object Detection using Deep-Learning and OpenCV", International Research Journal of Engineering and Technology (IRJET), 2020, Volume 7, issue 4, pp 3243-3246.
[5]	Mahadevi Parande and Shridevi Soma, "Concealed Weapon Detection in a Human Body by Infrared Imaging," International Journal of Science and Research (IJSR), Volume 4 Issue 9, September 2015, 182 – 188.
[6]	A. Agurto and et al., "A Review of Concealed Weapon Detection and Research in Perspective," 2007 IEEE International Conference on Networking, Sensing and Control, London, 2007, pp. 443-448.
[7]	Joseph Redmon and et al., "You Only Look Once: Unified, Real-Time Object Detection," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 779-788.
[8]	Kamble K. and et al., "Threat Detection with Facial Expression and Suspicious Weapon," Applied Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 1155. Springer, Singapore, 2020.
[9]	C. Papageorgiou and T. Poggio, “A Trainable System for Object Detection," International Journal of Computer Vision 38, 15–33 (2000).
[10]	P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, Kauai, HI, USA, 2001, pp. I-I.
[11]	T. Vijayakumar and R. Vinothkanna. "Retrieval of complex images using visual saliency guided cognitive classification." Journal of Innovative Image Processing (JIIP) (2020) Vol. 02/ No. 02 Pages: 102-109.
[12]	Vinothkanna R. "A Survey on Novel Estimation Approach of Motion Controllers for Self-Driving Cars." Journal of Electronics and Informatics (2020) Vol. 02/ No. 04 Pages: 211-219.

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APA Style

Sakib-Ahmod, Shoyaib Mahmud, Shammir Hossain, Yeasin Arafat, Jakia Rawnak Jahan, et al. (2021). Weapons Detection of Criminal Activities Based on Computer Vision. Advances, 2(4), 64-67. https://doi.org/10.11648/j.advances.20210204.11

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ACS Style

Sakib-Ahmod; Shoyaib Mahmud; Shammir Hossain; Yeasin Arafat; Jakia Rawnak Jahan, et al. Weapons Detection of Criminal Activities Based on Computer Vision. Advances. 2021, 2(4), 64-67. doi: 10.11648/j.advances.20210204.11

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AMA Style

Sakib-Ahmod, Shoyaib Mahmud, Shammir Hossain, Yeasin Arafat, Jakia Rawnak Jahan, et al. Weapons Detection of Criminal Activities Based on Computer Vision. Advances. 2021;2(4):64-67. doi: 10.11648/j.advances.20210204.11

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@article{10.11648/j.advances.20210204.11,
  author = {Sakib-Ahmod and Shoyaib Mahmud and Shammir Hossain and Yeasin Arafat and Jakia Rawnak Jahan and Ohidujjaman and Raihana Zannat},
  title = {Weapons Detection of Criminal Activities Based on Computer Vision},
  journal = {Advances},
  volume = {2},
  number = {4},
  pages = {64-67},
  doi = {10.11648/j.advances.20210204.11},
  url = {https://doi.org/10.11648/j.advances.20210204.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.advances.20210204.11},
  abstract = {In contemporary the term 'computer vision' is applicable vastly for significant research arena. Many researchers have a keen interest in this field. In this computer vision-based system, there have managed to detect weapons of two types (different guns and knives) to inform the concerned authority of property about crimes ongoing inside the place. While a property is under such criminal activity that the criminals carry guns or/and knives with them, the system detects those weapons through a camera integrated module and runs the necessary functions accordingly. Due to witnessing weapons, the system immediately informs the concerned authority to alert them about the upcoming risk to the property via mobile message and call. Consequently, the proprietor is alerted about the forthcoming risk and takes possible measures to handle the situation. Apart from that, the system can make sound alarms around the place of crime so that the people near to the property can come forward to help. This research is applicable in various properties such as banks, offices, homes or anywhere to protect the valuable properties from being theft or robbed. In this research computer vision and machine learning approaches are applied for the optimal result prediction.},
 year = {2021}
}

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TY  - JOUR
T1  - Weapons Detection of Criminal Activities Based on Computer Vision
AU  - Sakib-Ahmod
AU  - Shoyaib Mahmud
AU  - Shammir Hossain
AU  - Yeasin Arafat
AU  - Jakia Rawnak Jahan
AU  - Ohidujjaman
AU  - Raihana Zannat
Y1  - 2021/11/17
PY  - 2021
N1  - https://doi.org/10.11648/j.advances.20210204.11
DO  - 10.11648/j.advances.20210204.11
T2  - Advances
JF  - Advances
JO  - Advances
SP  - 64
EP  - 67
PB  - Science Publishing Group
SN  - 2994-7200
UR  - https://doi.org/10.11648/j.advances.20210204.11
AB  - In contemporary the term 'computer vision' is applicable vastly for significant research arena. Many researchers have a keen interest in this field. In this computer vision-based system, there have managed to detect weapons of two types (different guns and knives) to inform the concerned authority of property about crimes ongoing inside the place. While a property is under such criminal activity that the criminals carry guns or/and knives with them, the system detects those weapons through a camera integrated module and runs the necessary functions accordingly. Due to witnessing weapons, the system immediately informs the concerned authority to alert them about the upcoming risk to the property via mobile message and call. Consequently, the proprietor is alerted about the forthcoming risk and takes possible measures to handle the situation. Apart from that, the system can make sound alarms around the place of crime so that the people near to the property can come forward to help. This research is applicable in various properties such as banks, offices, homes or anywhere to protect the valuable properties from being theft or robbed. In this research computer vision and machine learning approaches are applied for the optimal result prediction.
VL  - 2
IS  - 4
ER  -

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Author Information

Sakib-Ahmod

Department of Computer Science & Engineering, Daffodil International University, Dhaka, Bangladesh
Shoyaib Mahmud

Department of Computer Science & Engineering, Daffodil International University, Dhaka, Bangladesh
Shammir Hossain

Department of Computer Science & Engineering, Daffodil International University, Dhaka, Bangladesh
Yeasin Arafat

Department of Computer Science & Engineering, Daffodil International University, Dhaka, Bangladesh
Jakia Rawnak Jahan

Department of Computer Science & Engineering, Daffodil International University, Dhaka, Bangladesh
Ohidujjaman

Department of Computer Science & Engineering, Daffodil International University, Dhaka, Bangladesh
Raihana Zannat

Department Software Engineering, Daffodil International University, Dhaka, Bangladesh

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APA Style

Sakib-Ahmod, Shoyaib Mahmud, Shammir Hossain, Yeasin Arafat, Jakia Rawnak Jahan, et al. (2021). Weapons Detection of Criminal Activities Based on Computer Vision. Advances, 2(4), 64-67. https://doi.org/10.11648/j.advances.20210204.11

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ACS Style

Sakib-Ahmod; Shoyaib Mahmud; Shammir Hossain; Yeasin Arafat; Jakia Rawnak Jahan, et al. Weapons Detection of Criminal Activities Based on Computer Vision. Advances. 2021, 2(4), 64-67. doi: 10.11648/j.advances.20210204.11

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AMA Style

Sakib-Ahmod, Shoyaib Mahmud, Shammir Hossain, Yeasin Arafat, Jakia Rawnak Jahan, et al. Weapons Detection of Criminal Activities Based on Computer Vision. Advances. 2021;2(4):64-67. doi: 10.11648/j.advances.20210204.11

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@article{10.11648/j.advances.20210204.11,
  author = {Sakib-Ahmod and Shoyaib Mahmud and Shammir Hossain and Yeasin Arafat and Jakia Rawnak Jahan and Ohidujjaman and Raihana Zannat},
  title = {Weapons Detection of Criminal Activities Based on Computer Vision},
  journal = {Advances},
  volume = {2},
  number = {4},
  pages = {64-67},
  doi = {10.11648/j.advances.20210204.11},
  url = {https://doi.org/10.11648/j.advances.20210204.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.advances.20210204.11},
  abstract = {In contemporary the term 'computer vision' is applicable vastly for significant research arena. Many researchers have a keen interest in this field. In this computer vision-based system, there have managed to detect weapons of two types (different guns and knives) to inform the concerned authority of property about crimes ongoing inside the place. While a property is under such criminal activity that the criminals carry guns or/and knives with them, the system detects those weapons through a camera integrated module and runs the necessary functions accordingly. Due to witnessing weapons, the system immediately informs the concerned authority to alert them about the upcoming risk to the property via mobile message and call. Consequently, the proprietor is alerted about the forthcoming risk and takes possible measures to handle the situation. Apart from that, the system can make sound alarms around the place of crime so that the people near to the property can come forward to help. This research is applicable in various properties such as banks, offices, homes or anywhere to protect the valuable properties from being theft or robbed. In this research computer vision and machine learning approaches are applied for the optimal result prediction.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Weapons Detection of Criminal Activities Based on Computer Vision
AU  - Sakib-Ahmod
AU  - Shoyaib Mahmud
AU  - Shammir Hossain
AU  - Yeasin Arafat
AU  - Jakia Rawnak Jahan
AU  - Ohidujjaman
AU  - Raihana Zannat
Y1  - 2021/11/17
PY  - 2021
N1  - https://doi.org/10.11648/j.advances.20210204.11
DO  - 10.11648/j.advances.20210204.11
T2  - Advances
JF  - Advances
JO  - Advances
SP  - 64
EP  - 67
PB  - Science Publishing Group
SN  - 2994-7200
UR  - https://doi.org/10.11648/j.advances.20210204.11
AB  - In contemporary the term 'computer vision' is applicable vastly for significant research arena. Many researchers have a keen interest in this field. In this computer vision-based system, there have managed to detect weapons of two types (different guns and knives) to inform the concerned authority of property about crimes ongoing inside the place. While a property is under such criminal activity that the criminals carry guns or/and knives with them, the system detects those weapons through a camera integrated module and runs the necessary functions accordingly. Due to witnessing weapons, the system immediately informs the concerned authority to alert them about the upcoming risk to the property via mobile message and call. Consequently, the proprietor is alerted about the forthcoming risk and takes possible measures to handle the situation. Apart from that, the system can make sound alarms around the place of crime so that the people near to the property can come forward to help. This research is applicable in various properties such as banks, offices, homes or anywhere to protect the valuable properties from being theft or robbed. In this research computer vision and machine learning approaches are applied for the optimal result prediction.
VL  - 2
IS  - 4
ER  -

Copy | Download