Application of Principal Component Analysis for Face Recognition Based on Weighting Matrix Using Gui Matlab


  • Y.A. Lesnussa
  • N.A. Melsasail
  • Z.A. Leleury


PCA, weighting matrix, face recognition


The increasingly widespread of using computers in daily life has brought the piranti as assistant for human. One of the application computer in the field of security has increased it is role is in terms of facial recognition. Face recognition is the process of human identification with the face image. With the increasingly widespread use of computers, is expected to face recognition capabilities can be adapted on the smart device. The adaption process became possible with the discovery of variety of facial recognition methods, one of which is the Principal Component Analysis (PCA). Research began by designing a computer program using the programming language Matlab. The program is used to test the results of PCA with several facial image. At the end it can be concluded that PCA is quite worthy of a face recognition method. The research data shows recognition results were pretty good with quite small error rate.


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How to Cite

Lesnussa, Y., Melsasail, N., & Leleury, Z. (2016). Application of Principal Component Analysis for Face Recognition Based on Weighting Matrix Using Gui Matlab. EDUCATUM Journal of Science, Mathematics and Technology, 3(2), 1–7. Retrieved from