A Comparison Study On Pca_Modular Pca And Lda For Face Recognition

Cheah, Boon Wah (2017) A Comparison Study On Pca_Modular Pca And Lda For Face Recognition. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik & Elektronik. (Submitted)

Download (975kB) | Preview


Face recognition has been considered as a popular technique to recognise identity of a person. Many face recognition algorithms have been developed and modified by researchers. This paper will study the performance of three face recognition algorithms which are PCA, Modular PCA and LDA. These three face recognition algorithms will be implement to determine which algorithm has the best performance. The performance of these face recognition algorithms will be evaluated by 10-fold cross validation using ORL database. K-fold technique will divide the image database into k-fold that has the same size or segment. Nine-fold will be used for training sets and the remaining one-fold will be used as validation sets to calculate the accuracy of the system. PCA is known as eigenface projection to transfer the image space to low dimension feature space. Modular PCA is to divide an image into sub-image and then apply PCA on it. LDA is used to separate two or more class further and enclose population in the class. The recognition rate for PCA, Modular PCA and LDA is 96.25%, 85.75% and 89%, respectively.

Item Type: Monograph (Project Report)
Subjects: T Technology
T Technology > TA Engineering (General). Civil engineering (General) > TA401-492 Materials of engineering and construction. Mechanics of materials
Divisions: Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraaan Elektrik & Elektronik (School of Electrical & Electronic Engineering) > Monograph
Depositing User: Mr Mohamed Yunus Mat Yusof
Date Deposited: 13 Jun 2022 01:03
Last Modified: 13 Jun 2022 01:03
URI: http://eprints.usm.my/id/eprint/52839

Actions (login required)

View Item View Item