Enhanced Security Through Real-Time Face Recognition: A Deepfacenet Approach for Video Surveillance Systems

Authors: Dr. G. Krishnapriya, M. Shalini

DOI Link: https://doi.org/10.22214/ijraset.2025.67045

Conclusion

In conclusion, deploying a DeepFace-based video surveillance system shows a notable improvement in real-time security for locations that are prone to crime. The suggested technique improves the detection and identification of known criminals with high accuracy by utilizing deep learning for facial recognition. This system addresses the latency and reliability issues of traditional surveillance by maintaining high processing rates and providing timely alerts with down-sampling techniques and a face tracking scoring mechanism. All things considered, this approach offers to improve public safety by proactively preventing events and providing law enforcement and security workers in crucial, high-risk situations with reliability

References

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Copyright

Copyright © 2025 Dr. G. Krishnapriya, M. Shalini. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Paper Id : IJRASET67045

Publish Date : 2025-02-20

ISSN : 2321-9653

Publisher Name : IJRASET

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