Design of Face Recognition Door Locking System
Student: Joel Ufot Amos (Thesis, 2025)
Department of Computer Engineering
Hussaini Adamu Federal Polytechnic, Kazaure, Jigawa State
Abstract
In recent times, there has been a growing interest in smart home systems particularly with the advent of Internet of Things (IOT). One of the important aspects of the smart home system is the security and access control. In this paper, a facial recognition security system was designed using ESP32 Camera which can be seamlessly integrated to the smart home system. Eigenface was used for the feature extraction, while Principal Component Analysis (PCA) was used as the classifier. The output of facial recognition algorithm was connected to the relay circuit which controls a motor lock placed at the door. Overall results obtained were very promising with 90% accuracy in facial recognition. Facial recognition accuracy can be improved by employing a hierarchical image processing approach to reduce the training or testing time.
Keywords
For the full publication, please contact the author directly at: amosjoel06@gmail.com
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- Landmark University, Omu-Aran, Kwara State 1
- Lead City University, Ibadan, Oyo State 1
- Lens Polytechnic, offa, Kwara State. 215
- Madonna University, Elele, Rivers State 20
- Madonna University, Okija, Anambra State 2
- Mcpherson University, Seriki Sotayo, Ogun State 1
- Michael and Cecilia Ibru University, Owhrode, Delta State 1
- Michael Okpara University of Agriculture, Umudike 43
- Michael Otedola Col of Primary Educ. Epe, Lagos (affl To University of Ibadan) 8
- Modibbo Adama University, Yola, Adamawa State 15