• Volume: 1
• Issue:02
• Date: 01-02-2024

Title : An Analytical Review of Real-Time Image Processing for Automated Criminal Identification Systems

Abstract: The rapid advancements in image processing and artificial intelligence have significantly enhanced the ability to identify and track criminal activities in real-time. Automated criminal identification systems leverage real-time image processing to analyze surveillance footage, facial recognition data, and other visual inputs for efficient and accurate identification of individuals involved in unlawful activities. This review provides a comprehensive analysis of the state-of-the-art techniques, algorithms, and frameworks utilized in real-time image processing for criminal identification. It explores the integration of deep learning, neural networks, and machine vision technologies that enable highspeed data processing and accuracy in dynamic environments. The paper also discusses challenges such as scalability, data privacy, false positives, and the ethical implications associated with the deployment of such systems. By critically examining current advancements and limitations, this review aims to provide insights into the potential improvements and future directions for developing more robust and ethical automated criminal identification systems.

Key Words: Real-time image processing, Automated criminal identification, Facial recognition, Deep learning, Neural networks, Machine vision, Surveillance systems, Crime detection technologies, Data privacy

Area: Engineering

• Approved ISSN: ----
• Paper Id: IJREISTU18
• Page No: 21-26

• Author: Bhad Sainath Asharam

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• Co- Author: Mr. Jeetendra Singh Yadav