A Review on The Comparison of Global Features Based Techniques LDA, PCA, and LBP Algorithm for Face Recognition

Volume 3 Issue 3 September - November 2016

Review Paper

A Review on The Comparison of Global Features Based Techniques LDA, PCA, and LBP Algorithm for Face Recognition

Rachana Dewangan*, Swati Verma**

* PG Student, Department of Electronics and Telecommunication Engineering, Shri Shankaracharya Technical Campus, Bhilai, India.

** Assistant Professor, Department of Electronics and Telecommunication Engineering, Shri Shankaracharya Technical Campus, Bhilai, India.

Dewangan, R., and Verma, S. (2016). A Review On The Comparison Of Global Features Based Techniques Lda, Pca, And Lbp Algorithm For Face Recognition. i-manager’s Journal on Pattern Recognition, 3(3), 32-38. https://doi.org/10.26634/jpr.3.3.12409

Abstract

Nowadays, face recognition has become very much popular to recognize a person with their face in order to avoid crime, etc. This mechanism is based on the division of the face, processing into three phases, i.e. face detection, feature extraction based on the input face image, and face recognition. In this paper, the authors have compared three algorithms, such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Patterns (LBP). The rate of accuracy of face recognition has also been compared. The advantages and disadvantages of these algorithms will help in obtaining a solution, so that a better face recognition system can be designed.