Copyright © 2026 Authors retain the copyright of this article. This article 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.

@article{176735,
        author = {Darshanala Kiran Kumar and Mohd. Sirajuddin and Jilladwar Sagar and Singapuram Rishikesh},
        title = {RealTime Detection of Accused Persons Using Computer Vision and Deep Learning Models},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {7261-7266},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176735},
        abstract = {This project addresses the escalating concerns surrounding increasing crime rates and the challenges faced by law enforcement in ensuring public safety. In response to the limitations of manpower, the project introduces a real time accused person detection system utilizing CCTV technology, computer vision, and facial recognition algorithms. The system captures live video feeds, employs advanced face recognition techniques, and matches detected faces against a database of known accused individuals. Implemented in Python using OpenCV and face recognition libraries, the system operates in real time, integrating seamlessly with existing surveillance infrastructure. Alerts are triggered upon identifying a match, providing law enforcement with relevant information for rapid response. Extensive testing demonstrates the system's effectiveness and adaptability across diverse scenarios, showcasing its practical viability as a proactive tool for crime prevention and the apprehension of individuals with a history of criminal accusations in public spaces. This project contributes significantly to enhancing public safety and law enforcement capabilities.},
        keywords = {Community security; Criminal activity reduction; Crime deterrence; Face identification; Legal enforcement; Machine vision; Monitoring systems; OpenCV framework; Policing and investigation; Preventive technology; Suspect identification; Video surveillance systems.},
        month = {April},
        }