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.
Keywords
Face Recognition, Real-Time Authentication, Python, OpenCV Library, Security
Citations
IRE Journals:
Swathi M, Akshay A, Hemalatha M, Janani G, K Vidhyaroshini "Smart Vision: Real-Time Person Identification System" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 81-88 https://doi.org/10.64388/IREV9I6-1712552
IEEE:
Swathi M, Akshay A, Hemalatha M, Janani G, K Vidhyaroshini
"Smart Vision: Real-Time Person Identification System" Iconic Research And Engineering Journals, 9(6) https://doi.org/10.64388/IREV9I6-1712552
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IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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