IMPLEMENTATION OF FACE RECOGNITION USING GEOMETRIC FEATURES EXTRACTION
DOI:
https://doi.org/10.21107/kursor.v11i2.284Keywords:
biometrics, Euclidean distance, face recognition, feature extraction, real-timeAbstract
The face is among the biometric objects used to recognize one’s identity. There are various face recognition system methods that can be applied, one of which is geometric features-based face recognition. Geometric features are unique features extraction of one’s facial components. These features are obtained by calculating the comparison values of the distance measurement between facial components served as a reference like eyes, nose, and mouth. This research implemented a face recognition system using the geometric features method on a significantly low-spec computer system. This implementation was carried out by building a system, installing it on a computer system, and then testing it using laptops or computer devices and the camera web. The face recognition system would process the facial input images, extract their geometric features, and match the results with the data stored in the database. The research results were a low-spec computer system that could recognize its users by providing real-time feedback in the form of users’ names with an accuracy of 98%.
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[3] W. Zhao, R. Chellappa, P. J. Phillips, and A. A. Rosenfield, “Face Recognition: A Literature Survey,†ACM Computing Surveys, vol. 35, no. 4, pp. 399-458, 2003.
[4] J. A. Andre, "Sistem Security Webcam Dengan Menggunakan Microsoft Visual Basic (6.0)," Jurnal Teknologi dan Sistem Informasi UNIVRAB, 2016.
[5] D. A. Prasetya and I. Nurviyanto, "Deteksi Wajah Metode Viola Jones Pada OpenCV Menggunakan Pemrograman Python," Simp. Nas. RAPI XI FT UMS, pp. 18-23, 2013.
[6] Kholistianingsih, "Ekstraksi Ciri Geometris Untuk Pengenalan Wajah," Fakultas Teknik Universitas Gadjah Mada, Yogyakarta, 2012.
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[8] T. E. Prabowo, R. Hartanto and S. Wibirama, "Pengembangan Purwarupa Aplikasi Presensi Mahasiswa Dteti Ugm Berbasis Pengenalan Wajah Menggunakan Algoritme Eigenface," Departemen Teknik Elektro dan Teknologi Informasi, Yogyakarta, 2019.
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[11] S. Z. Li and A. K. Jain, “Handbook of Face Recognition,†Springer, 2011.
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