International Scientific Journal of Engineering and Management

An International Scholarly || Multidisciplinary || Open Access || Indexing in all major Database & Metadata
The journal follows the UGC Guidelines and is evaluated for inclusion in the Web of Science
ISSN: 2583-6129

Impact Factor: 7.839

Biometric Attendance Monitoring Using Iris Recognition Technology

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“Biometric Attendance Monitoring Using Iris Recognition Technology"

 

Saurabh Namdev Khaire, Dr. Amit. Bhusari

 1Saurabh khaire Master of Computer Application & Trinity Academy of Engineering, Pune

  2 Dr.Amit. Bhusari Master of Computer Application & Trinity Academy of Engineering, Pune

 

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Abstract - In modern institutions and organizations, ensuring accurate and secure attendance tracking remains a significant challenge. Traditional methods such as manual roll calls or card-based systems are often prone to errors, fraud, and inefficiencies. Biometric-based attendance monitoring system utilizing iris recognition technology, offering a secure, non-invasive, and highly accurate solution biometric attendance monitoring system based on iris recognition technology. The proposed system offers a secure, efficient, and contactless method of recording attendance, overcoming the limitations of traditional methods such as manual entry and RFID cards. By utilizing the uniqueness and stability of the human iris, the system ensures high accuracy and resistance to spoofing. The research discusses the design, development, and performance evaluation of the system, incorporating image processing and pattern recognition algorithms. Experimental results demonstrate the system's effectiveness in real-world conditions, highlighting its potential for applications in educational institutions, corporate offices, and secure facilities.

The proposed system captures and verifies the unique iris patterns of individuals to record attendance in real-time. Leveraging image processing and pattern recognition algorithms, the system ensures high matching accuracy while mitigating the risk of impersonation.

 

Key Words:  Biometric authentication, Iris recognition, Attendance system, Image processing, Pattern recognition, Security, Automation.

 


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