SISTEM PENGENALAN WAJAH DENGAN METODE EUCLIDEN DISTANCE

Dedy Harto, Muhammad Zaki Rahmani

Abstract


Biometrics is computer technology for the recognition of oneself through certain body parts. The use of pupil eyes as a feature of a person is the result of extracting facial features using geometry features, measurement of distance between eyes is still manually so that it requires a system that directly displays the results of measurements to obtain PD values that can be directly used to identify someone. This study designed a face recognition system through the MATLAB GUI to simplify the process of image capture and processing. The image is taken using a smartphone that is connected directly to a portable computer wirelessly through the Internet Protocol Camera system. The number of image samples used amounted to 50 samples for the database and 100 samples for the test data consisting of 10 people with the composition of 5 men and 5 women. Image processing uses the Viola-Jones method to detect faces in the second area of the eye and uses the Euclidean distance method to find the pupillary distance value which is then followed by image grouping based on that range of values and ends with facial recognition system testing. The test uses 100 samples of image data consisting of 5 men and 5 women with each of the 10 image data. Based on the results of these tests, the accuracy of face recognition system is obtained by 73% and the accuracy value based on gender for men is 78% and women are 68%. With face matching speed of about 2-3 seconds..


Keywords


PD (Pupillary Distance); geometri; GUI MATLAB; viola-jones; euclidean distance;

Full Text:

PDF

References


Darma putra, Sistem Biometrika (Konsep Dasar, Teknik Analisa Citra, dan Tahapan Membangun Aplikasi Sistem Biometrika). Yogyakarta: penerbit andi, 2009.

H. . Fatta, Rekayasa Sistem Pengenalan Wajah, 1st ed. Yogyakarta: penerbit andi, 2009.

N. Dodgson, Variation and extrema of human interpupillary distance, vol. 5291. 2004.

R. W. A. Puri, “Pengenalan wajah menggunakan alihragam wavelet haar dan jarak euclidien,†J. Tek. Elektro, vol. 0, pp. 1–7, 2010.

M. S. Anam and S. Islam, “Face recognition using genetic algorithm and back propagation neural network,†Proc. …, vol. I, pp. 18–21, 2009.

Ahsanul Intishor, “Pengenalan Wajah dengan Menggunakan Metode Centroid dan Geometric Mean,†Universitas Islam Negei Maulana Malik Ibrahim Malang Untuk, 2015.

ILHAM ANDRIAN, “PERBANDINGAN METODE VIOLA JONES dengan METODE ROBERTS CROSS pada sistem PENGENALAN WAJAH,†J. Chem. Inf. Model., vol. 53, no. 9, pp. 1689–1699, 2013.

D. Nugraheny, “Metode Nilai Jarak Guna Kesamaan Atau Kemiripan Ciri Suatu Citra (Kasus Deteksi Awan Cumulonimbus Menggunakan Principal Component Analysis),†Angkasa J. Ilm. Bid. Teknol., vol. 7, no. 2, p. 21, 2017.

F. A. Hermawati, Pengolahan Citra Digital, 1st ed. Yogyakarta: penerbit andi, 2011.

V. S. T d Sutoyo, Edy Mulyanto, Teori Pengolahan Citra Digital, 1st ed. Yogyakarta: Penerbit Andi, 2009.

Sahid, Pengantar Komputasi Numerik dengan MATLAB, 1st ed. Yogyakarta: penerbit andi, 2005.

Y. N. Erick Paulus, cepat mahir GUI Matlab, 1st ed. Yogyakarta: penerbit andi, 2007.




DOI: https://doi.org/10.35334/jeb.v5i2.1045

Refbacks

  • There are currently no refbacks.


Address:

Gedung D Lt. 3 Kampus Universitas Borneo Tarakan. Jl. Amal Lama No. 1, Tarakan, Kalimantan Utara, Indonesia. Kodepos: 77123.

Email:elektrika@borneo.ac.id
Hp :+62 813-5064-4775

 

All Publications

by JEB (Jurnal Elektrika Borneo)

are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License