Smart Vision: Real-Time Person Identification System

Face recognition is an advanced technology that combines image processing and machine learning to identify or verify an individual based on facial features. The objective of this project is to design and implement a reliable face recognition system using Python and OpenCV. The system captures realtime images through a webcam and detects faces using the Haar Cascade algorithm. It then extracts unique facial features and compare them with the trained dataset for accurate identification. Once the user is recognized, their details such as name and contact information are displayed on the interface. This system can be applied in areas like attendance monitoring, security systems, and authorized access control, where user authentication is essential. The project provides a cost-effective, automated, and user-friendly solution to replace traditional identification methods while maintaining high accuracy and reliability. The proposed system eliminates the need for traditional passwordbased authentication, reducing security risks such as password theft or duplication. Experimental results demonstrate that the system achieves high accuracy and fast recognition time, making it suitable for real-world, real-time environments.

Publication Details

Journal
Iconic Research and Engineering Journals
Published
2025-12-02
DOI
https://doi.org/10.64388/irev9i6-1712552
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Vision: Real-Time Person Identification System

Iconic Research and Engineering Journals
Face recognition and analysis
article

Smart Vision: Real-Time Person Identification System

article en

Abstract

Face recognition is an advanced technology that combines image processing and machine learning to identify or verify an individual based on facial features. The objective of this project is to design and implement a reliable face recognition system using Python and OpenCV. The system captures realtime images through a webcam and detects faces using the Haar Cascade algorithm. It then extracts unique facial features and compare them with the trained dataset for accurate identification. Once the user is recognized, their details such as name and contact information are displayed on the interface. This system can be applied in areas like attendance monitoring, security systems, and authorized access control, where user authentication is essential. The project provides a cost-effective, automated, and user-friendly solution to replace traditional identification methods while maintaining high accuracy and reliability. The proposed system eliminates the need for traditional passwordbased authentication, reducing security risks such as password theft or duplication. Experimental results demonstrate that the system achieves high accuracy and fast recognition time, making it suitable for real-world, real-time environments.

Iconic Research and Engineering JournalsVol. 9(6)
Openalex Percentile: Top 59%
Face recognition and analysis
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Smart Vision: Real-Time Person Identification System · Iconic Research and Engineering Journals (2025) | TGRS Research Map | TGRS