Pengenalan Wajah Manusia Dengan Variasi Pencahayaan Menggunakan Metode Local Binary Pattern (LBP)
DOI:
https://doi.org/10.22441/jte.2020.v11i3.003Kata Kunci:
Local Binary Pattern, Matlab, Extended Yale B, k-Nearest Neighbor, Pra ProsesAbstrak
Sistem pengenalan wajah adalah teknik biometrik yang memungkinkan komputer atau mesin untuk mengenal wajah manusia melalui sebuah gambar digital dengan cara mencocokan pola wajah dengan basis data yang tersimpan. Sistem pengenalan wajah variasi pencahayaan mempunyai kendala pada performa sistem pengenalan wajah, terutama pada pencahayaan. Contoh kasus nya ada pada sebuah smartphone yang mempunyai masalah pada sistem pengenalan wajah pada kondisi ruangan yang gelap. Penelitian ini bertujuan untuk mengembangkan sistem pengenalan wajah dalam permasalahan variasi pencahayaan agar dapat meningkatkan performa keakuratan sistem pengenalan wajah dalam mengenal wajah pengguna smartphone. Sistem ini akan menggunakan metode Local Binary Pattern (LBP), dan akan di kombinasikan dengan beberapa Pra Proses, yaitu Ekualisasi Histogram, Sharpening, Gaussian Filter, dan Median Filter yang berfungsi sebagai ekstrasi fitur dalam pengenalan wajah manusia dengan variasi pencahayaan. Kemudian sistem ini menambahkan fitur klasifikasi menggunakan metode Nearest Neightbor yang berfungsi untuk pengklasifikasian wajah manusia ke dalam class class yang sudah ditentukan.Unduhan
Referensi
R. Purwati, & G. Ariyanto. “Pengenalan Wajah Manusia Berbasis Algoritma Local Binary Pattern”. Emitor: Jurnal Teknik Elektro, 17(2), 29-38 .2018
Muljono, T. Sutojo and A. N. Pulung. “Pengolahan Citra Digital”. Penerbit Andi. P.34. 2017
R. C. Gonzalez, R. E. Woods and S. L. Eddins. “Digital image processing using MATLAB”. Pearson Education India. 2004
Fajriana, F. Wahyu, and Sadli. “Aplikasi Penerapan Auto Matic Clustering dan Fuzzy Time Series”. Yayasan Kita Menulis, P. 77-78. 2019
A. S. Georghiades, P. N. Belhumeur and D. J. Kriegman, “From few to many: illumination cone models for face recognition under variable lighting and pose,” in IEEE Trans. Pattern Anal. And machine Intell., Vol. 23, no. 6, Jun 2001, pp. 643-660.
K. C. Lee, J. Ho and D. J. Kriegman, “Acquiring linier subspaces for face recognition under variabel lighting,” in IEE Trans. Pattern Anal. And machine Intell,. Vol. 27, no. 5, May 2005,pp. 684-698
Unduhan
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
The copyright to this article is transferred to Universitas Mercu Buana (UMB) if and when the article is accepted for publication. The undersigned hereby transfers any and all rights in and to the paper including without limitation all copyrights to UMB. The undersigned hereby represents and warrants that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required. The undersigned represents that he/she has the power and authority to make and execute this assignment.
We declare that:
1. This paper has not been published in the same form elsewhere.
2. It will not be submitted anywhere else for publication prior to acceptance/rejection by this Journal.
3. A copyright permission is obtained for materials published elsewhere and which require this permission for reproduction.
Furthermore, I/We hereby transfer the unlimited rights of publication of the above mentioned paper in whole to UMB. The copyright transfer covers the exclusive right to reproduce and distribute the article, including reprints, translations, photographic reproductions, microform, electronic form (offline, online) or any other reproductions of similar nature.
The corresponding author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors. This agreement is to be signed by at least one of the authors who have obtained the assent of the co-author(s) where applicable. After submission of this agreement signed by the corresponding author, changes of authorship or in the order of the authors listed will not be accepted.
Retained Rights/Terms and Conditions
1. Authors retain all proprietary rights in any process, procedure, or article of manufacture described in the Work.
2. Authors may reproduce or authorize others to reproduce the Work or derivative works for the authors personal use or for company use, provided that the source and the UMB copyright notice are indicated, the copies are not used in any way that implies UMB endorsement of a product or service of any employer, and the copies themselves are not offered for sale.
3. Although authors are permitted to re-use all or portions of the Work in other works, this does not include granting third-party requests for reprinting, republishing, or other types of re-use.
