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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | FACE RECOGNITION ATTENDANCE |
| Authors Name: | Pooja , Jean Celia Grace , Rajalakshmi , Rathi Jasna |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_219584
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| Published Paper Id: | IJNRD2404672 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Attendance monitoring is a critical function in educational institutions and organizational settings, serving as a cornerstone for ensuring accountability, optimizing resource allocation, and fostering productivity. Traditional methods of attendance tracking, such as manual roll calls and barcode scanners, are often labor- intensive, error-prone, and susceptible to fraudulent practices. In response to these challenges, the development of facial recognition technology has emerged as a promising solution, offering the potential to revolutionize attendance monitoring through automation and increased accuracy. This paper introduces a Facial Recognition Attendance Monitoring System designed to address the limitations of conventional attendance tracking methods. The system leverages cutting-edge advancements in computer vision and machine learning to provide a robust and reliable mechanism for recording attendance. By integrating Tkinter for desktop interface and a web interface, the system ensures seamless accessibility and usability for both staff and students across diverse platforms. At the heart of the system lies its ability to accurately detect and identify individuals based on their unique facial features. Utilizing sophisticated techniques such as the Haar Cascade classifier and LBPH algorithm, the system can perform real-time face detection and recognition from video streams captured by standard web cameras. This enables swift and efficient attendance tracking without the need for manual intervention. Key features of the system include a user-friendly interface for face registration, allowing individuals to quickly enroll their faces and associated personal information. Additionally, the system is designed to be scalable, capable of accommodating varying user volumes to meet the needs of educational institutions and organizations of all sizes. The effectiveness of the Facial Recognition Attendance Monitoring System is demonstrated through detailed descriptions of its architecture, implementation methodology, and evaluation results. Empirical findings indicate significant improvements in attendance management processes, including enhanced accuracy, reduced administrative burdens, and streamlined operations. Overall, this paper highlights the transformative potential of facial recognition technology in attendance monitoring, offering insights into its practical applications and implications for educational institutions and organizational stakeholders. |
| Keywords: | FACE RECOGNITION ATTENDANCE |
| Cite Article: | "FACE RECOGNITION ATTENDANCE", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.g601-g611, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404672.pdf |
| Downloads: | 00052 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2404672 Registration ID: 219584 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: g601-g611 Country: -, -, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404672 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404672 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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