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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Volume 11 | Issue 7
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Impact Factor : 8.14
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| Paper Title: | Adaptive LBPH: A Dynamic Feature Extraction Technique for Real-Time Face-Based Attendance System |
| Authors Name: | Jyoti Varshney , Mr. B. L. Pal |
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IJRTI_213106
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| Published Paper Id: | IJRTI2606005 |
| Published In: | Volume 11 Issue 6, June-2026 |
| DOI: | |
| Abstract: | Attendance management in educational institutions remains a critical administrative challenge, with traditional manual and biometric methods being susceptible to proxy attendance, human error, and unhygienic physical contact. This paper presents an Adaptive Local Binary Pattern Histogram (Adaptive LBPH) framework for a real-time face recognition-based attendance system. Unlike conventional single-model LBPH approaches, the proposed methodology trains three LBPH classifiers concurrently using distinct radius values (R=1, R=2, R=3) with corresponding neighbor configurations (P=10, P=12, P=14), enabling multi-scale facial texture feature extraction. During real-time recognition, predictions from all three models are aggregated through a majority voting mechanism, followed by average confidence evaluation against a calibrated threshold (T=110). A frame-based stability validation module ensures attendance is marked only upon consistent recognition across three consecutive video frames, significantly mitigating false positives caused by lighting variation, motion blur, and occlusion. The system is implemented using Python, OpenCV, Tkinter, and MySQL, operating on standard CPU-based hardware without GPU support. Experimental evaluation demonstrates overall recognition accuracy in the range of 94–98% under normal classroom conditions, with effective unknown-face rejection (~95%) and reliable duplicate attendance prevention. The proposed system offers a computationally efficient, cost-effective, and practically deployable solution for real-time attendance automation in educational institutions. |
| Keywords: | Face Recognition, Adaptive LBPH, Multi-Model LBPH, Haar Cascade, Stable Frame Validation, Attendance Management System, OpenCV, Real-Time Recognition, Majority Voting, Confidence Thresholding. |
| Cite Article: | "Adaptive LBPH: A Dynamic Feature Extraction Technique for Real-Time Face-Based Attendance System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 6, page no.a52-a66, June-2026, Available :http://www.ijrti.org/papers/IJRTI2606005.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 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: IJRTI2606005
Registration ID:213106
Published In: Volume 11 Issue 6, June-2026
DOI (Digital Object Identifier):
Page No: a52-a66 Country: Aligarh, Uttar Pradesh, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2606005 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2606005 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
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