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Project Overview: ATLAS (Attendance Tracking & Live Verification System)

This project was actually developed regarding from these issues and its solution:

Issues:

  • Inconvenient & Inefficient Workflow: The interns must waiting for manual logbook queue at guard post.
  • Security Risks: The risk of missing logbook or even damaged logbook.

Solution:

By implementing Face Recognition System, ATLAS can eliminate those issues and digitizes the attendance process, data integrity through any local databases (I'm using SQLite in this case) and providing a seamless user experience.


The theory that I've implemented on this project

1. The ROI (Region of Interest) Layout

To improve accuracy in crowded environments, ATLAS utilizes an oval-shaped ROI layout. This ensures the system focuses only on the primary user in front of the camera, preventing "false triggers" from background movement or other people passing by.

2. Recognition Logic & Euclidean Principles

The system calculates the similarity between faces using Euclidean distance algorithms. To ensure high reliability, I implemented a strict Confidence Threshold logic:

Threshold Range Status Action
< 0.50 Match Found Attendance recorded successfully.
0.50 - 0.65 ⚠️ Low Confidence System prompts user to try a different angle.
> 0.65 Unknown Face isn't recognized in the database.

Note: A lower threshold indicates a higher degree of similarity between the detected face and the database record.


Main Features

  • Real-time Face Detection: Agile and accurate recognition using OpenCV, Pickle and Face Recognition Libraries.
  • Sleek UI: Clean and understandable UI by providing oval layout in the middle and feedback UI made with Tkinter.
  • Downloadable Logs: Effortless exportable logs and automatically converted to Excel format.
  • Local Databases Integration: Secure interns log & profiles.
  • Secure Exportable Logs: Protected system with hardcoded secrets for downloading those logs.

Technologies that I've used for this project

Component Technology
Language Python
AI/ML OpenCV, Face Recognition
Database SQLite
GUI Tkinter
Others Pickle, Pillow, Numpy

Project Architecture

To ensure the system runs efficiently as I expected, so, I've designed these workflow for this project.

Entity Relationship Diagram (ERD)

ERD

Flowchart

Flowchart

Unfortunately, these Project Architecture are still written in Indonesian and not in English yet.


Miscellaneous

Screenshot 2026-02-23 082807

About

An attendance app using Face Recognition technology made with Python, Tkinter and Face Recognition Libraries.

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