Criminal Investigation Tracker with Suspect Prediction

Author:

Pradeep T Sam,Tejavardhan Reddy Badugula,Manikanta Jagarapu,Dinesh Kumar Voleti,SaiTheja Sannapaneni

Abstract

This initiative seeks to craft an inclusive and intuitive web-based platform tailored for criminal identification via image and video surveillance, leveraging cutting-edge facial recognition technology. The system integrates a registration portal for inputting data and images of known criminals, utilizing OpenCV and advanced facial recognition algorithms to securely analyze and store their facial attributes. In addition to allowing users to upload images for analysis, the system offers immediate feedback on potential matches with registered criminals. Moreover, the video surveillance module extends this capability to short videos, employing video analytics to identify faces within the footage. The platform ensures real-time feedback for successful identifications and provides an advanced feature enabling users to download details of identified criminals in an Excel format. By amalgamating state-of-the-art technology with an intuitive interface, this project endeavors to bolster law enforcement endeavors by furnishing an efficient and precise tool for criminal identification and tracking. Its objectives encompass developing a robust system for identifying and tracking criminals through advanced facial recognition algorithms and OpenCV technology, designing a user-friendly web interface for seamless navigation across various modules, and establishing a secure and efficient registration section for compiling comprehensive databases of facial features.

Publisher

International Journal of Innovative Science and Research Technology

Reference26 articles.

1. Mohler, G. O., Short, M. B., Malinowski, S., Johnson, M., Tita, G. E., Bertozzi, A. L., & Brantingham, P. J. (2015). Randomized controlled field trials of predictive policing. Journal of the American Statistical Association, 110(512), 1399-1411.

2. Ratcliffe, J. H. (2016). Intelligence-led policing. Routledge.

3. Mohler, G. O., & Short, M. B. (2019). Criminal forecasting: past, present, and future. Annals of the American Association of Geographers, 109(2), 446-454.

4. Lum, K., & Isaac, W. (2016). To predict and serve?. Significance, 13(5), 14-19.

5. Groff, E. R., & La Vigne, N. G. (2002). Forecasting the future of predictive crime mapping. Crime Prevention Studies, 13, 71-98.

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