Browse By Repository:

 
 
 
   

Online Face Recognition System Using Artificial Neural Network

Ch'ng, Yau Yau (2015) Online Face Recognition System Using Artificial Neural Network. Project Report. UTeM, Melaka, Malaysia. (Submitted)

[img] Text (24 Pages)
Online Face Recognition System Using Artificial Neural Network.pdf - Submitted Version

Download (348Kb)

Abstract

Biometric recognition system such as facial recognition system was widely developed over the past few years. Facial recognition system is commonly used in security system to allow user to protect their privilege. Most of users wanted their information and place to be secure with a trusted security system. The normal security like key or password is no longer relevant as people prefer an easier and flexible way. Therefore, this thesis presents a better and easier way of security system that can recognize the user successfully and give the matching percentage. By using Radial Basis Function Neural Network in MATLAB, a face recognition system can be created. RBFNN will detect face from image captured by camera; it will turn it into grayscale, cropped it and save as a dimension of 50*50 pixels sized picture. That picture will be normalized and reshaped into one column matrix form of 1*n data. The RBF system will be trained by data as reference, input image will undergo the same process and the data obtained will be used to match with the data in the RBF to obtain the matching percentage. 200 inputs of user and 160 inputs of non-users were used to test on the system for false acceptance rate and false rejection rate. A suitable matching percentage reference was chosen from this analysis as the minimum require matching to access the security system where error rate is one of the main concerns where it is the unwanted result that might occur. Different threshold number, spread value, and sizes of dimension also tested, the differences on the output matching result were observed. By using the microcontroller to control a relay to control the magnetic door lock, the system was able to successfully control the door lock. The benefits of this online face recognition system is used human own natural facial as a password for the security system. This system can be applied at office, lecturers‘ room, or even at house.

Item Type: Monograph (Project Report)
Uncontrolled Keywords: Biometric identification
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Library > Projek Sarjana Muda > FTK
Depositing User: Mohd Hannif Jamaludin
Date Deposited: 10 Oct 2016 00:30
Last Modified: 10 Oct 2016 00:30
URI: http://eprints.utem.edu.my/id/eprint/17305

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year