Automated Biometric AI Attendance

Next-Gen Face Recognition
Attendance System

Fast, touchless, and secure attendance verification powered by OpenCV computer vision and machine learning. Register employee or student face biometrics, verify presence instantly, and track complete attendance records.

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Live Attendance Feed 05 Oct 2026

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Recognition Engine
OpenCV LBPH Active
Mark Attendance

Users can scan their face via real-time webcam or upload a photo. The system identifies the individual and logs timestamped presence into MySQL.

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Register Face & Profile

Enroll students and employees with unique alphanumeric IDs, role, and department. Validates frontal face quality before saving to the biometric dataset.

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Admin Dashboard

Login-protected administration portal with full attendance history logs, search filters, date queries, user profile management, and CSV export.

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ARCHITECTURE

How Face Attendance Operates

A streamlined 3-step workflow combining PHP, Python, and OpenCV machine vision.

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1. Enrolment & Indexing

User uploads face photo or captures via webcam. The system detects the facial region, normalizes dimensions to 200x200, and stores in /uploads/faces/.

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2. Facial Feature Matching

During attendance, the target face is matched against the trained LBPH dataset via a Python sub-process, checking texture histograms and cross-correlation.

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3. Automated Logging

Upon positive match verification, an attendance record is created in MySQL with user_id, date, time, status, and confidence level.