Face Recognition Implementation System As A Media Access To Restricted Room With Histogram Equalization And Fisherface Methods
| Autor: | Eka Wahyu Aditya, Mardlijah, Mat Syai'in, Joko Aji Saputro, Gaguk Suharjito, Ruddianto, Muhammad Khoirul Hasin, R.T. Soelistijono, Lilik Subiyanto, Usman Dinata, Nur Tsalis Taufiqur Rahman, E. A. Zuliari, Fathulloh |
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| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Record locking Computer science business.industry Process (computing) 02 engineering and technology Linear discriminant analysis Facial recognition system 020901 industrial engineering & automation Face (geometry) Personal computer Principal component analysis 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Histogram equalization |
| Zdroj: | 2019 International Symposium on Electronics and Smart Devices (ISESD). |
| DOI: | 10.1109/isesd.2019.8909665 |
| Popis: | The face is one of the easiest way to identify individual and to distinguish. Therefore, the face recognition system is usually needed in the security system in the restricted rooms of the company. This research is to minimize all fraudulent actions such as theft of the company data. In this final project, the method used is histogram equalization and fisherface. The main step in this security system is that the user's face will be taken using a webcam. Then the process of face recognition uses the histogram equalization and the fisherface method using a PC (Personal Computer). Fisherface is a combination of Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) methods. When an RFID sensor matches the employee data, the camera will capture and the process of face recognition will be run. After that the face data will be matched with the existing face data. When the both is match, the PC sends a command to the Arduino microcontroller to open the solenoid door lock. So that the security systems through face recognition can be more effective than conventional security systems. The test result of the face recognition system which has been done in this Final Project, has a success rate of 88.33% which was obtained from 120 times of experiments consisted of 12 poses. The test success level of the security system with 3 correspondents was 88.33%. |
| Databáze: | OpenAIRE |
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