IMPLEMENTASI SISTEM PENGENALAN WAJAH UNTUK KEAMANAN AKSES BERBASIS UBUNTU MENGGUNAKAN PYTHON

Fahrizal fahrizal fahrizal

Abstract


Security is one of the most important needs for human beings in both the building and the house. For the development of security technology used face recognition. Face recognition is a system that identifies facial features that are capable of detecting familiar faces and unknown faces. In this research is implemented with computer vision where the computer can see and understand so that it is information from an image or video. This computer can also mimic the ability of human intelligence. To classify a face object, OpenCv uses the Haar Cascade classifier and uses Python programming language. Application used face Recognition program is PyCharm Comunity 2018 version 3 with Linux operating system Ubuntu 18.04.2 LTS version. The results showed that the accuracy of face reconition depends on the analysis of OpenCv and the classification of Cascade for computer vision process.



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References


C. J., & Cheng, Q. (2014). Computer vision. In Food Engineering Series. https://doi.org/10.1007/978-1-4939-0311-5_7

Purwanto, P., Dirgantoro, B., & Jati, A. N. (2015). Implementasi Face Identification Dan Face Recognition Pada Kamera Pengawas Sebagai Pendeteksi Bahaya. EProceedings of Engineering, 2(1), 718–724. Retrieved from https://libraryeproceeding.telkomuniversity.ac.id/index.php/engineering/article/view/2045

Shell, S. (2014). An introduction to Numpy and Scipy. University of California, Santa Barbara.

Syafira, A. R., & Ariyanto, G. (2018). Sistem Deteksi Wajah Dengan Modifikasi Metode Viola Jones. Jurnal Emitor.

Unpingco, J. (2014). Python for Signal Processing. In Python for Signal Processing. https://doi.org/10.1007/978-3-319-01342-8

Wang, Y.-Q. (2014). An Analysis of the Viola-Jones Face Detection Algorithm. Image Processing On Line. https://doi.org/10.5201/ipol.2014.104

Wahyono, Teguh. 2018. Fundamental Of Python For Machine Learning (Dasar-Dasar Pemrograman Python Untuk Machine Learning dan Kecerdasan Buatan. Yogyakarta: Penerbit Gava Media.

Suprianto Dodit, Hasanah Rini Nur, S. Purnomo Budi. 2013. Sistem Pengenalan Wajah Secara Real-Time dengan Adaboost, Eigenface PCA & MySQL. Jurnal EECCIS Vol. 7, No. 2.

Kurniawan Luthfi Maslichul. 2014. Metode Face Recognition untuk Identifikasi Personil Berdasar Citra Wajah bagi Kebutuhan Presensi Online Universitas Negeri Semarang. Scientific Journal of Informatics Vol. 1, No. 2

Munawir, Fitria Liza, Hermansyah Muhammad. 2020. implementasi Face Recognition Pada Absensi Kehadiran Mahasiswa Menggunakan Metode Haar Cascade Classifier. InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan).

Beysolow II, T. (2018). Applied Natural Language Processing with Python. In Applied Natural Language Processing with Python. https://doi.org/10.1007/978-1-4842-3733-5




DOI: http://dx.doi.org/10.31000/jika.v5i2.4509

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