COMPARISON OF EIGENFACE AND FISHERFACE METHODS FOR FACE RECOGNITION

  • Elly Firasari universitas nusa mandiri
  • F Lia Dwi Cahyanti
  • Fajar Sarasati
  • Widiastuti Widiastuti
DOI: https://doi.org/10.33480/techno.v19i2.3470
Keywords: Haar Cascade Classifier, Eigenface, Fisherface,

Abstract

Abstract— Biometric information systems have been widely used in the fields of government, shopping centers, education and even security, which offer biological authentication so that the system can recognize its users more quickly. The parts of the human body are identified by a biometric system that has unique and specific characteristics, one of which is the face. Adjustment of facial image deals with objects that are never the same, due to the parts that can change. These changes are caused by facial expressions, light intensity, shooting angle, or changes in facial accessories. With this, the same object with several differences must be recognized as the same object. In this study, the data used were 388 face images and the sata test consisted of 30 face images. Before the face is tested, preprocessing and feature extraction are carried out using the Haar Cascade Classifier and then detected using Eigenface and Fisherface. Based on the research results, the Fisherface method is an algorithm that is accurate and efficient compared to the Eigenface algorithm. The Fisherface algorithm has an accuracy of 88%. while the Eigenface method has an accuracy rate of 76%.

Keywords – Haar Cascade Classifier, Eigenface, Fisherface,.

Published
2022-09-30
How to Cite
Firasari, E., Cahyanti, F. L., Sarasati, F., & Widiastuti, W. (2022). COMPARISON OF EIGENFACE AND FISHERFACE METHODS FOR FACE RECOGNITION. Jurnal Techno Nusa Mandiri, 19(2), 125 - 130. https://doi.org/10.33480/techno.v19i2.3470
Issue
Vol 19 No 2 (2022): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of September 2022
Section
Articles

Copyright (c) 2022 Elly Firasari, F Lia Dwi Cahyanti, Fajar Sarasati, Widiastuti

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

The copyright of any article in the TECHNO Nusa Mandiri Journal is fully held by the author under the Creative Commons CC BY-NC license.

  1. The copyright in each article belongs to the author.
  2. Authors retain all their rights to published works, not limited to the rights set out on this page.
  3. The author acknowledges that Techno Nusa Mandiri: Journal of Computing and Information Technology (TECHNO Nusa Mandiri) is the first to publish with a Creative Commons Attribution 4.0 International license (CC BY-NC).
  4. Authors can enter articles separately, manage non-exclusive distribution, from manuscripts that have been published in this journal into another version (for example: sent to author affiliation respository, publication into books, etc.), by acknowledging that the manuscript was published for the first time in Techno Nusa Mandiri: Journal of Computing and Information Technology (TECHNO Nusa Mandiri);
  5. The author guarantees that the original article, written by the stated author, has never been published before, does not contain any statements that violate the law, does not violate the rights of others, is subject to the copyright which is exclusively held by the author.
  6. If an article was prepared jointly by more than one author, each author submitting the manuscript warrants that he has been authorized by all co-authors to agree to copyright and license notices (agreements) on their behalf, and agrees to notify the co-authors of the terms of this policy. Techno Nusa Mandiri: Journal of Computing and Information Technology (TECHNO Nusa Mandiri) will not be held responsible for anything that may have occurred due to the author's internal disputes.