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Percentage Completed : 65%

Project Description

This project proposes a new system for taking attendance in offices, industries, organizations and companies using facial recognition technology controlled by a Raspberry pi 4 with 1.5GHZ processor. The Raspberry pi 4 has 8GB RAM memory that will be used to achieve a high speed of operation and accuracy. It uses QT creator for creating and running the application of face recognition system. It contains OpenCV for image processing application to load the images into the system and process the images. This proposed face recognition based attendance management system with Raspberry pi 4 using Eigen faces algorithm. Eigen face algorithm is highly secured, highly efficient and accurate. The module detects the images of staff’s face captured by the camera, which have been stored manually with their names and file numbers in the system database. Using the stored database, all the details like date, time and present or absentee are well recorded.

Project Aim

The aim of this project is to design a high tech facial recognition attendance register with database management system that will help in adequate monitoring of staffers attendance to work.

Project Economic Importance

• It is low-cost and small size system • It is hassle-free; it reduces human intervention in its mode of operation • The use of hardware such as finger print scanners, palm-print scanners, DNA analyzer is not required • It can be inserted into wooden/metal doors • It has good recognition rate with 95% accuracy and the recognition is less than 0.5s • Power efficiency

Project Team

Engr. Nneka Ezeani, Engr. Chijioke Dilibe, Engr. Timothy Babalola, Engr. Theresa Chime

Dated Started : 2022-03-15

Percentage Completed : 65%

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