Can Similarity Measures Techniques be Used to Model Face Recognition?

Year 2022, Volume: 3 Issue: 2, 70 - 75, 28.12.2022

Enes Algül

Abstract

Facial recognition is used efficiently in human-computer interactions, passports, driver’s licence, border controls, video surveillance and criminal identification, and is an important biometric’s security option in many device-related security requirements. In this paper, we use Eigenface recognition based on the Principal Component Analysis (PCA) to develop the project. PCA aims to reduce the size of large image matrices and is used for feature extraction. Then, we use the euclidean distance method for classification. The dataset used in this project was obtained by AT&T Laboratories at Cambridge University [1]. The training dataset contains grayscale facial images of 40 people; each person has 10 different facial images taken from different angles and emotions.
This study aims to give researchers a hunch before they start to develop image recognition using deep learning methods. It also shows that face recognition can be done without deep learning.

Keywords

Eigenface, PCA, Classification, Facial Recognition, Distance Methods

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