Real Time Crime Detection and Face Recognition System Using CNN

P Meenakshi Devi, K Shanmuga Priya, T Nandhini, J Gladson, K Gowsikk Kumar, R Joshan Pravin Kumar

2025

Abstract

The point of this study is to develop an ongoing thief location and face recognition framework utilizing Convolutional Neural Networks (CNN) to upgrade precision and speed. The exhibition of the proposed CNN-based framework is contrasted with the YOLOv3 model concerning discovery precision and handling speed. Materials and Methods: The investigation incorporates two get-togethers: Group 1 involves the proposed CNN-based bad behavior identification and face verification system with 10 test samples, while Group 2 tends to the YOLOv3-based structure with 10 test samples. The quantifiable power is set to 80%, with a significance edge of (p<0.05) and a conviction time period. Result: The proposed crime detection system using a CNN has greater accuracy and also faster processing in comparison to Hear Cascade and Single Shot Detector (SSD)-based approaches. The accuracy of the CNN is around 96.5 % to 97.5 %, whereas that of the methods based on the Haar Cascade and Single Shot Detector (SSD) achieved accuracy of between 84.3 % to 87.5 %. In ideal lighting and frontal facial views, the highest level of accuracy has been noticed for CNN than 0.05 level of significance for the CNN. Conclusion: According to this study, the system of real-time crime detection with face recognition done using CNN technology performs the best as compared to traditional methods of Haar Cascade and Single Shot Detector (SSD). The speed and accuracy are higher in this case, and therefore, it is a reliable solution for many crime detection applications.

Paper Citation

in Harvard Style

Meenakshi Devi P., Shanmuga Priya K., Nandhini T., Gladson J., Gowsikk Kumar K. and Joshan Pravin Kumar R. (2025). Real Time Crime Detection and Face Recognition System Using CNN. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 602-608. DOI: 10.5220/0013902600004919

in Bibtex Style

@conference{icrdicct`2525,
author={P Meenakshi Devi and K Shanmuga Priya and T Nandhini and J Gladson and K Gowsikk Kumar and R Joshan Pravin Kumar},
title={Real Time Crime Detection and Face Recognition System Using CNN},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={602-608},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013902600004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Real Time Crime Detection and Face Recognition System Using CNN
SN - 978-989-758-777-1
AU - Meenakshi Devi P.
AU - Shanmuga Priya K.
AU - Nandhini T.
AU - Gladson J.
AU - Gowsikk Kumar K.
AU - Joshan Pravin Kumar R.
PY - 2025
SP - 602
EP - 608
DO - 10.5220/0013902600004919
PB - SciTePress