Secure Sight: Real-Time Criminal Identification and Tracking System

Authors: Om Bankar, Kaushal Chandratre, Sahil Badgujar, Tanuja Bhalerao, Prof. Pranali Shinde

Country: India

Full-text Research PDF File:   View   |   Download

Abstract: This project is to develop an advanced criminal identification system leveraging deep learning techniques to enhance the efficiency and accuracy of suspect identification for law enforcement, military, and security forces. Despite the adoption of various technologies, existing systems often struggle with visual data that is limited or of poor quality. To address this, the proposed solution employs a combination of Convolutional Neural Networks (CNN) and the Histogram of Oriented Gradients (HOG) algorithm to analyze key visual features, including facial characteristics. By focusing on improving performance under challenging conditions, this system is designed to be applicable in real-world scenarios. Additionally, the project will investigate the integration of the identification system into existing security frameworks, aiming to create a scalable, reliable tool that can operate in real-time or near-real-time, thereby supporting quick and informed decision-making by authorities.

Keywords:

Paper Id: 232369

Published On: 2025-04-11

Published In: Volume 13, Issue 2, March-April 2025

Share this