MATLAB Implementation of Face Identification using Principal Component Analysis

被引：0
|
作者：
Mahmood, Nasrul Humaimi [1 ]
Ariffin, Ismail [1 ]
Omar, Camallil [1 ]
Jaafar, Nur Sufiah [1 ]
机构：
[1] Univ Teknol Malaysia, Biomed Instrumentat & Elect Res Grp, Dept Elect, Fac Elect Engn, Utm Johor Bahru 81310, Malaysia
来源：
MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8 | 2012年 / 433-440卷
关键词：
PCA algorithm; Face Identification; Webcam; Biometrics; MATLAB;
D O I：
10.4028/www.scientific.net/AMR.433-440.5402
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Face is the greatest superior biometric as the face has a complex, multidimensional and meaningful identity compared from one person to another. Face identification is executed by comparing the characteristics of the face (test image) with those of known individual images in the database. This paper describes the used of the Principal Component Analysis (PCA) algorithm for human face identification based on webcam image. The MATLAB is used as a tool for image processing and analysis. The important decision to identify the person is by the minimum distance of the face images and known face images in face space. From the results, it can be concluded that the work has successfully implemented the PCA algorithm for human face identification through a webcam.
引用
收藏
页码：5402 / 5408
页数：7
相关论文
共 50 条
  • [1] Face Recognition on Surgically Altered Faces using Principal Component Analysis
    George, Giji
    Boben, Rainu
    Radhakrishnan, B.
    Suresh, L. Padma
    PROCEEDINGS OF 2017 IEEE INTERNATIONAL CONFERENCE ON CIRCUIT ,POWER AND COMPUTING TECHNOLOGIES (ICCPCT), 2017,
  • [2] A MATLAB toolbox for Principal Component Analysis and unsupervised exploration of data structure
    Ballabio, Davide
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2015, 149 : 1 - 9
  • [3] Comparing The Performance of Principal Component Analysis and RBF Network for Face Recognition Using Locally Linear Embedding
    Abusham, Eimad E. A. A.
    Ngo, David
    Teoh, Andrew
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2006, 6 (04): : 25 - 29
  • [4] Icatoolbox2.0.:: A matlab implementation of independent component analysis algorithms
    Górriz, JM
    Méndez, JC
    Proceedings of the Fourth IASTED International Conference on Modelling, Simulation, and Optimization, 2004, : 124 - 128
  • [5] Sign Language Recognition Using Principal Component Analysis
    Saxena, Ankita
    Jain, Deepak Kumar
    Singhal, Ananya
    2014 FOURTH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES (CSNT), 2014, : 810 - 813
  • [6] FACE RECOGNITION Using MATLAB
    Obagbuwa, Ibidun Christiana
    Bam, Stefany
    Moroka, Dineo Tiffany
    2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI 2021), 2021, : 1744 - 1747
  • [7] Hidden Markov Models & Principal Component Analysis for Multispectral Palmprint Identification
    Meraoumia, Abdallah
    Korichi, Maarouf
    Chitroub, Salim
    Bouridane, Ahmed
    2015 5TH INTERNATIONAL CONFERENCE ON INFORMATION & COMMUNICATION TECHNOLOGY AND ACCESSIBILITY (ICTA), 2015,
  • [8] Implementation of a Face Recognition System Based on Matlab and LabVIEW
    Zhang, Tao
    Cui, Yanqiu
    Yang, Yaning
    PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON MECHATRONICS, MATERIALS, CHEMISTRY AND COMPUTER ENGINEERING 2015 (ICMMCCE 2015), 2015, 39 : 357 - 360
  • [9] Principal component analysis - a tutorial
    Tharwat, Alaa
    INTERNATIONAL JOURNAL OF APPLIED PATTERN RECOGNITION, 2016, 3 (03) : 197 - 240
  • [10] Biometrics Based Attendance Checking using Principal Component Analysis
    Dela Cruz, Jennifer C.
    Paglinawan, Arnold C.
    Bonifacio, Miguel Isiah R.
    Flores, Allan Jake D.
    Hurna, Earl Vic B.
    2015 IEEE REGION 10 HUMANITARIAN TECHNOLOGY CONFERENCE (R10-HTC), 2015,
12345