Septian Adi Wijaya – Informatics Brawijaya University PERBANDINGAN METODE PENGENALAN WAJAH SECARA REAL-TIME PADA PERANGKAT BERGERAK BERBASIS ANDROID Septian Adi Wijaya – Informatics Brawijaya University

Main Idea To implemented face recognition application on smart-phone Doing recognition with 3 different method Compare accuracy rate of 3 face recognition’s method Main Idea

Introduction & Motivation Why Face Recognition? Motivation for using LBPH, PCA and LDA Introduction & Motivation

Two modes of Face Recognition IDENTIFICATION To recognize “who is X?” Executed by system with compared a “one-to- many” search VERIFICATION To answer question “is this X?” Executed by system with compared a “one-to- one” search Two modes of Face Recognition

Five Step Process

What’s the different? LBPH LBP LBPH Method

Facial Representation Using LBPH Image divided into many region Each pixel of region transformed into binary number by circular extended-LBP Binary number that produced then transformed again into decimal Decimal number then be next center of pixel & produce histogram (bin range 0-255) Facial Representation Using LBPH

Facial Representation Using LBPH Calculate total bins of histogram then subtracted to another. the smallest value result of subtracted then it’ll classify to it’s label image. *note: get sum histogram of image, then subtract it with other = …? Facial Representation Using LBPH

Extended-LBP Extend value of radius and sample point P = Sample Point, R = Radius in my paper used P=16 & R=2 and divided 16x16 region Extended-LBP

f PCA Method Treat pixel as a vector Compute mean on image with configure principal component then represent with matrix f PCA Method

PCA Algorithm Compute covarian matrix Compute eigenvalue and eigenvector vi from S Sorting to the largest of eigenvalue  eigenvector Compute with Euclidean distance to classify image PCA Algorithm

LDA Method Focused on dimensional reduction Algorithm on LDA almost resemble with PCA Calculation on mean computed per-class LDA Method

Facial Representation Using LDA Compute mean total of all class Compute mean each class *note: N is number various of class yi is column vector *note: Yi is number of class yi is column vector Facial Representation Using LDA

Looking for the largest matrix each class LDA Algorithm

LDA Algorithm Compute eigenvalue. Next step almost same on PCA algorithm LDA Algorithm

Methodology

Based on testing step that have done with 75 training image (@class 25 image) 25 testing image with time range 5s, 10s, 15s and 20s Result

Accuracy Rate

The larger range time for testing image the larger accuracy rate we get LBPH method is the most suitable for computation on mobile android Conclusion

Thanks…