A Study for Face Recognition Using Techniques PCA and KNN

EasyChair Preprint 4931

Abstract

Face recognition has now become one of the interesting fields of research and has received a substantial attention of researchers from all over the world. Face recognition techniques has been mostly used in the discipline of image analysis, image processing, etc. This paper provides various techniques which are often used for face recognition in face recognition systems. In this paper performance of face recognition with two well-known image recognition methods such as Principal Component Analysis (PCA) and K-Nearest Neighbour (KNN). The effectiveness of color information plays an important role when face images are taken under strong variation in illumination, as well as low spatial resolution. In this paper, we improve a face recognition system using Principal Component Analysis (PCA) to extract features from the face images and reduce the dimensionality of each image and K nearest neighbour to classify data.

Keyphrases: Face Recognition Technique, Face recognition system, K-Nearest Neighbour (KNN), Principal Component Analysis (PCA), face detection, face recognition, recognition system

@booklet{EasyChair:4931,
  author    = {Prachi Sasankar and Usha Kosarkar},
  title     = {A Study for Face Recognition Using Techniques PCA and KNN},
  howpublished = {EasyChair Preprint 4931},
  year      = {EasyChair, 2021}}