Web-Based Face Recognition using Line Edge Detection and Euclidean Distance Method

Authors

DOI:

https://doi.org/10.29408/edumatic.v6i1.5525

Keywords:

euclidean distance, face recognition, line edge detection, search system

Abstract

A face recognition system is to perform a match face image using the face extraction method. There are many applications used in various algorithms and implemented in many programming languages, but still difficult to implement on web-based applications using the PHP programming language. The purpose of this research is to produce a website-based application focused on the face recognition section. The author will limit the system only to detect the front view of the face, the main goal is to get a fairly high level of accuracy. There will be a feature to find where the face is located. The research method used is a laboratory experiment where the search system scheme based on face recognition will produce the appearance of several faces that have the closest Euclidean distance values from grades 1st to 5th. The results from the comparison of the test image with the training image based on Line Edge Detection and Euclidean Distance calculation concluded that the system can be implemented in searching of similarity and recognizing the face.

References

Abidin, S. (2018). Deteksi Wajah Menggunakan Metode Haar Cascade Classifier Berbasis Webcam Pada Matlab. Jurnal Teknologi Elekterika, 15(1), 21–27. https://doi.org/10.31963/elekterika.v15i1.2102

Alam, M. J., & ShahzahanAli, T. C. M. (2020). A smart login system using face detection and recognition by ORB algorithm. Indonesian Journal of Electrical Engineering and Computer Science, 20(2), 1078-1087. https://doi.org/10.11591/ijeecs.v20.i2.pp1078-1087

Archilles, A., & Wicaksana, A. (2020). Vision: a web service for face recognition using convolutional network. TELKOMNIKA (Telecommunication Computing Electronics and Control), 18(3), 1389-1396. https://doi.org/10.12928/TELKOMNIKA.v18i3.14790

Gao, Y., & Leung, M. K. H. (2002). Face recognition using line edge map. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(6), 764–779. https://doi.org/10.1109/TPAMI.2002.1008383

Hidayat, W., Utami, E., Iskandar, A. F., Hartanto, A. D., & Prasetio, A. B. (2021). Perbandingan Performansi Model pada Algoritma K-NN terhadap Klasifikasi Berita Fakta Hoaks Tentang Covid-19. Edumatic: Jurnal Pendidikan Informatika, 5(2), 167–176. https://doi.org/10.29408/edumatic.v5i2.3664

Kagawade, V. C., & Angadi, S. A. (2019). Multi-directional local gradient descriptor: A new feature descriptor for face recognition. Image and Vision Computing, 83–84(C), 39–50. https://doi.org/10.1016/j.imavis.2019.02.001

Khan, M. J., Khurshid, K., & Shafait, F. (2019). A spatio-spectral hybrid convolutional architecture for hyperspectral document authentication. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 1097–1102. https://doi.org/10.1109/ICDAR.2019.00178

Kusrini, W., Fathurrahmani, F., & Sayyidati, R. (2020). Sistem Pakar untuk Diagnosa Penyakit Ayam Pedaging. Edumatic: Jurnal Pendidikan Informatika, 4(2), 75–84. https://doi.org/10.29408/edumatic.v4i2.2616

Li, C., & Li, C. (2019). Web Front-End Realtime Face Recognition Based on TFJS. Proceedings 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI, 1–5. https://doi.org/10.1109/CISP-BMEI48845.2019.8965963

Lyanpen, W., Petrosyan, O. G., & Jianming, D. (2019). Face Recognition Based on the Coefficient Tree for Three Scale Wavelet Transformation. Automatic Control and Computer Sciences, 53(8), 995–1005. https://doi.org/10.3103/S0146411619080315

Mekala, V., Vinod, V. M., Manimegalai, M., & Nandhini, K. (2019). Face recognition based attendance system. International Journal of Innovative Technology and Exploring Engineering, 8(12), 520–525. https://doi.org/10.35940/ijitee.L3406.1081219

Nikhilesh, S. (2018). Face Recognition In Java Environment. International Journal of Advanced Multidisciplinary Scientific Research, 1(5), 46–49. https://doi.org/10.31426/ijamsr.2018.1.5.519

Nordin, N., & Fauzi, N. H. M. (2020). A web-based mobile attendance system with facial recognition feature. International Journal of Interactive Mobile Technologies, 14(5), 193–202. https://doi.org/10.3991/IJIM.V14I05.13311

Pang, J. Y., Low, K. Y., & Wong, H. L. (2019). Development of a multi-client student attendance monitoring system. International Journal of Recent Technology and Engineering, 8(3 Special Issue), 6–11. https://doi.org/10.35940/ijrte.C1002.1083S19

Pereira, P., & Kuhn, T. (2020). An Experimental Study of Face Recognition Method. Computer Science & IT Research Journal, 1(2), 52–58. https://doi.org/10.51594/csitrj.v1i2.135

Rahmadi, T., Ginting, G., & Fadlina. (2018). Identifikasi wajah manusia berdasarkan warna kulit dengan menggunakan transformasi wavelet. Pelita Informatika Budi Darma, 6(4), 394-397.

Rai, L., Wang, Z., Rodrigo, A., Deng, Z., & Liu, H. (2020). Software development framework for real-time face detection and recognition in mobile devices. International Journal of Interactive Mobile Technologies, 14(4), 103–120. https://doi.org/10.3991/IJIM.V14I04.12077

Saad, S. L., Kamal, M. M., & Zamri, N. A. (2019). Monitoring and complaining web-based face recognition using Haar-MATLAB. 8thIEEE International Conference on Control System, Computing and Engineering, ICCSCE, 206–211. https://doi.org/10.1109/ICCSCE.2018.8685017

Sutabri, T., Pamungkur, Kurniawan, A., & Saragih, R. E. (2019). Automatic attendance system for university student using face recognition based on deep learning. International Journal of Machine Learning and Computing, 9(5), 668–674. https://doi.org/10.18178/ijmlc.2019.9.5.856

Tabassum, F., Imdadul Islam, M., Tasin Khan, R., & Amin, M. R. (2022). Human face recognition with combination of DWT and machine learning. Journal of King Saud University - Computer and Information Sciences, 34(3), 546–556. https://doi.org/10.1016/j.jksuci.2020.02.002

Tuncer, T., Dogan, S., Abdar, M., Basiri, M. E., & Pławiak, P. (2019). Face recognition with triangular fuzzy set-based local cross patterns inwavelet domain. Symmetry, 11(6), 1–18. https://doi.org/10.3390/sym11060787

Wu, H., Cao, Y., Wei, H., & Tian, Z. (2021). Face Recognition Based on Haar like and Euclidean Distance. Journal of Physics: Conference Series, 1813(1), 1–7. https://doi.org/10.1088/1742-6596/1813/1/012036

Downloads

Published

2022-06-19

Issue

Vol. 6 No. 1 (2022): Edumatic: Jurnal Pendidikan Informatika

Section

Articles

License

Semua tulisan pada jurnal ini adalah tanggung jawab penuh penulis. Edumatic: Jurnal Pendidikan Informatika bisa diakses secara free (gratis) tanpa ada pungutan biaya, sesuai dengan lisensi creative commons yang digunakan.

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