Comparison of Different Face Recognition Method Based On PCA

Rajib Saha; Debotosh Bhattacharjee; Sayan Barman

doi:10.24297/ijmit.v10i4.626

Comparison of Different Face Recognition Method Based On PCA

Authors

Rajib Saha RCC Institute Of Information Technology, Kolkata, India
Debotosh Bhattacharjee Jadavpur University,Kolkata
Sayan Barman RCC Institute Of Information Technology, Kolkata,

DOI:

https://doi.org/10.24297/ijmit.v10i4.626

Keywords:

Eigenfaces, Eigenvector, Eigenvalue, PCA, Multiview, Euclidean distance, Chebychev distance, Manhattan distance

Abstract

This paper is about human face recognition in image files. Face recognition involves matching a given image with the database of images and identifying the image that it resembles the most. Here, face recognition is done using:

(a) Eigen faces and

(b) applying Principal Component Analysis (PCA) on image.

The aim is to successfully demonstrate the human face recognition using Principal component analysis & comparison of Manhattan distance, Eucleadian distance & Chebychev distance for face matching.

Downloads

Download data is not yet available.

Author Biographies

Rajib Saha, RCC Institute Of Information Technology, Kolkata, India

Department of Computer Science & Engineering ,

Assistant Professor

Debotosh Bhattacharjee, Jadavpur University,Kolkata

Department of Computer Science and Engineering,

Sayan Barman, RCC Institute Of Information Technology, Kolkata,

Department of Computer Science and Engineering,

Downloads

Published

2014-11-04

How to Cite

Saha, R., Bhattacharjee, D., & Barman, S. (2014). Comparison of Different Face Recognition Method Based On PCA. INTERNATIONAL JOURNAL OF MANAGEMENT &Amp; INFORMATION TECHNOLOGY, 10(4), 2016–2022. https://doi.org/10.24297/ijmit.v10i4.626