Oriental Journal of Computer Science and Technology

Open Access Open Access  Restricted Access Subscription Access

A Comparative Review on Different Methods of Face Recognition


Affiliations
1 Department of Computer Science, Master of Computer Application, Christ University, India
2 Department of Computer Science, Christ University, India
 

Face Recognition is a biometric system which can be used to identify or verify a person from digital image by using the facial features that are unique to each other. There are many techniques which can be used in a face recognition system. In this paper we review some of the algorithms and compare them to see which technique is better compared to one another. Techniques that are compared in this technique are Non-negative matrix factorization (NMF) with Support Vector Machine (SVM), Partial Least Squares (PLS) with Hidden Markov Model (HMM) and Local Ternary Pattern (LTP) with Booth’s Algorithm.

Keywords

Face Recognition, NMF, SVM, PLS, HMM, LTP, Booth Algorithm.
User
Notifications
Font Size

  • W Wei-Lun Chao, “Face Recognition”,GICE,National Taiwan University.

  • LianZhichao and ErMengJoo, “Face Recognition Under Varying Illumination”, NanyangTechnilogical University, Singapore.

  • Xia Sun, Qingzhou Zhang and Ziqiang Wang”Face Recognition Based on NMF and SVM”, Wuhan University of Technology and Henan University of Technology, China, 2009.

  • Y Yegang Hu, Benyong Liu “Face Recognition Based on PLS and HMM”,Guizhou University, China,2009.

  • Abdullah Gubbi, Mohammad FazleAzeem and Nishabanu Z H Nayakwadi “Face recognition using Local Ternary Pattern and Booth’s Algorithm”,3rd International Conference on Eco-Friendly Computing and Communication Systems, 2014.

  • Quanbin Li, ChuanweiSun,Jingao Liu “Illumination Invariant Face Recognition Based on ULBP and SVM”, JSNU, ECNU, China 5th International Conference on BioMedical Engineering and Informatics (BMEI 2012).

  • Swati Y.Raut, Dipti.A.Doshi “A Face Recognition System by Hidden Markov Model and Discriminating Set Approach”

  • MenakaRajapakse and Lonce Wyse “Face Recognition with Non-negative Matrix Factorization”,Institute for Infocomm Research, Singapore.

  • https://in.mathworks.com/help/stats/hidden-markov-models-hmm.html

  • K K. Srinivasa Reddy, V.Vijaya Kumar, B. Eswara Reddy “Face Recognition Based on Texture Features using Local Ternary Patterns”, Hyderabad, Hyderabad, A.P.,India.,2015


Abstract Views: 427

PDF Views: 5




  • A Comparative Review on Different Methods of Face Recognition

Abstract Views: 427  |  PDF Views: 5

Authors

Tenzin Dawa
Department of Computer Science, Master of Computer Application, Christ University, India
N. Vijayalakshmi
Department of Computer Science, Christ University, India

Abstract


Face Recognition is a biometric system which can be used to identify or verify a person from digital image by using the facial features that are unique to each other. There are many techniques which can be used in a face recognition system. In this paper we review some of the algorithms and compare them to see which technique is better compared to one another. Techniques that are compared in this technique are Non-negative matrix factorization (NMF) with Support Vector Machine (SVM), Partial Least Squares (PLS) with Hidden Markov Model (HMM) and Local Ternary Pattern (LTP) with Booth’s Algorithm.

Keywords


Face Recognition, NMF, SVM, PLS, HMM, LTP, Booth Algorithm.

References





DOI: https://doi.org/10.13005/ojcst%2F10.01.31