Perbandingan Pengenalan Citra Wajah Berbasis Reduksi Dimensionalitas dengan Principal Component Analysis (PCA) dan Jaringan Saraf Tiruan

Abstract

This paper will describes human face recognition
process using principal component analysis compared to artificial
intelligence network approach. The basic idea for this research is
dimensionality reduction of the image used for the recognition
system. Principal component analysis reduce the dimensionality
of image recognize using its eigen vector nd eigen value.
Dimensionality reduction used for Artificial Neural Network
based on image processing technique. This research suggest new
idea for using canny filter (edge detector) for dimensionality
reduction. Artificial Neural Network used in this experiment
based on backpropagation training. Experiment result for these
two approachs will be compared to recognize its performances.