DESAIN DAN IMPLEMENTASI SISTEM FACE RECOGNITION MENGGUNAKAN WEBCAM UNTUK PENGAMAN PINTU DENGAN METODE PRINCIPAL COMPONENT ANALYSIS

MONIKA, SINAR (2017) DESAIN DAN IMPLEMENTASI SISTEM FACE RECOGNITION MENGGUNAKAN WEBCAM UNTUK PENGAMAN PINTU DENGAN METODE PRINCIPAL COMPONENT ANALYSIS. Other thesis, POLITEKNIK NEGERI SRIWIJAYA.

[img]
Preview
Text (Cover)
file 1.pdf

Download (438kB) | Preview
[img]
Preview
Text (BAB I Pendahuluan)
file 2.pdf

Download (170kB) | Preview
[img]
Preview
Text (BAB II Tinjauan Pustaka)
file 3.pdf

Download (957kB) | Preview
[img] Text (BAB III Metodologi Penelitian)
file 4.pdf
Restricted to Repository staff only

Download (423kB) | Request a copy
[img] Text (BAB IV Hasil dan Analisa)
file 5.pdf
Restricted to Repository staff only

Download (901kB) | Request a copy
[img]
Preview
Text (BAB V Kesimpulan dan Saran)
file 6.pdf

Download (159kB) | Preview
[img]
Preview
Text (Daftar Pustaka)
file 7.pdf

Download (148kB) | Preview
[img]
Preview
Text
Lampiran - Mainform.pdf

Download (361kB) | Preview

Abstract

Face Recognition is to compare the input image with the database face and find the face that best suits the input image to be said to be recognized or not. Developed using Visual Studio Software and using arduinouno in order to identify the face that suits the database in realtime. There are 3 house owner in the database where each occupant has 30 facial image databases retrieved from webcam camera from front view, without using accessories, and without expression. Because the dimension of pixel result of big transformation then done dimension reduction by using method of Principal Component Analysis which also known as eigenface method. At the time of testing by using the method of Principal Component Analysis there are two stages when identifying the image of his face. The first stage is the preprocessing stage and the second stage is the introduction stage. After the image of the training is processed it will look for the average value if the input image close to the average value of the face image on the database and the image is recognized then arduino will give the command to open the prototype door. The success rate in this experiment is very good as expected and has a high degree of accuracy and rapid detection. The level of success depends on the lighting, the image factor being performed during the database retrieval process, the expression of the face, and the angle of the image.

Item Type: Thesis (Other)
Uncontrolled Keywords: Arduino Uno,Eigenface, Face Recognition, PCA, Visual Studio 2015
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Telecommunication Engineering > Undergraduate Theses
Depositing User: Mrs Trisni Handayani
Date Deposited: 03 May 2018 08:20
Last Modified: 03 May 2018 08:20
URI: http://eprints.polsri.ac.id/id/eprint/4516

Actions (login required)

View Item View Item