Sistem Deteksi Biometrik Keunikan Wajah Secara Real Time
Abstract
Facial recognition is important for identifying a person's biodata profile. The physical development of students from the time they entered college to graduation has experienced inconspicuous changes but it is sometimes difficult to identify faces one by one. Digital form is becoming a trend to remember more real time. An important part of human physical identification has begun to shift from signature - finger - face selection. The face includes five important senses that are interconnected into an identification device. In this study the focus is on face detection based on color, the application of the Camshift Algorithm and finding the distance between the face sensing points is the result of the Gabor Wavelet method. Training data uses 4-8 second real time video. The hue histogram is basically the same as the RGB histogram, the difference is that the hue histogram uses the Hue value instead of RGB because the hue value represents natural color without regard to lighting. Gabor Wavelet transform is provided to solve filter design problems. The face detection system looks for face points to form a frame-shaped face selection if previously the face has been stored in a database so the system can easily describe biodata. Face selection can be done on live testing data. The selection box detection follows every facial movement.
Keywords
Full Text:
PDFReferences
Sultoni, Hary Soekotjo Dachlan, Panca Mudjirahardjo, Rahmadwati, “Pengenalan Wajah Secarareal Time Menggunakan Metode Camshift, Lapalcian Of Gaussian Dan Discrete Cosine Transform Two Dimensional (LoGDCT2D)”, Jurnal Ilmiah NERO Vol. 2, No.3 hal : 153-160, tahun 2016.
Luki Wahyu Hendrawan, Mohammad Ramdhani, Dadan Nur Ramadan, “Rancang Bangun Sistem Pelacakan Objek Secara Real Time Berdasarkan Warna”, e-Proceeding of Applied Science : Vol.2, No.1 pp: 383-388, April 2016.
Naser Jawas, “Pelacakan Gerakan Tangan Untuk Pengenalan Gerak-Isyarat”, IT Journal, Vol. 5 No. 1, hal 13-23, April 2017.
Romi Wiryadinata, Raya Sagita, Siswo Wardoyo, Priswanto, “Pengenalan Wajah Pada Sistem Presensi Menggunakan Metode Dynamic Times Wrapping, Principal Component Analysis dan Gabor Wavelet”, Dinamika Rekayasa, vol 12, hal 1-8, Tahun 2016.
Adil Setiawan, “Penerapan Algoritma Gabor Wavelet Sebagai Keamanan Rumah Dengan Mengidentifikasi Wajah Berbasis Webcam”, Eksplora Informatika Vol. 5, No. 2, Maret 2016.
Andre Lukito Kurniawan, R. Rizal Isnanto, Ajub Ajulian Zahra, “Perancangan Sistem Pengenalan Wajah Menggunakan Metode Ekstraksi Ciri Susunan Tapis Wavelet Gabor 2D Dengan Jarak Euclidean”, TRANSIENT, vol 4, hal 2-5, 2015.
Aris Budi , Suma'inna, Hata Maulana, “Pengenalan Citra Wajah Sebagai Identifier Menggunakan Metode Principal Component Analysis (PCA)”, JURNAL TEKNIK INFORMATIKA, vol 9, hal 166-175, Tahun 2016.
. Sultoni, “Modifikasi Metode Camshift Untuk Pengenalan Citra Wajah Secara Real Time Berdasarkan Warna Kulit Wajah”, Seminar Nasional Inovasi Dan Aplikasi Teknologi di Industri 2017, hal 1-7, 2017.
. Jefry Sunupurwa Asri, Gerry Firmansyah, “Implementasi objek detection dan tracking menggunakan deep learning untuk pengolahan citra digital”. Konferensi Nasional Sistem Informasi 2018, STMIK Atma Luhur Pangkalpinang, 8 – 9, hal : 717-723, Maret 2018..
Andrean Hutama Koosasi, Riyanarto Sarno, dan Abdul Munif, “Deteksi Fraud Menggunakan Metode Model Markov Tersembunyi pada Proses Bisnis”, JURNAL TEKNIK ITS Vol. 6, hal 1-5, Tahun 2017.
Immanuela P. Saputro, Ernawati, B.Yudi Dwiandiyanta, “Pengenalan Ekspresi Wajah Menggunakan Wavelet Gabor Dan Backpropagation”, JURNAL ELEKTRO, Vol. 8, hal 71-78, Tahun 2015.
Anita Sindar RM Sinaga, Implementasi Teknik Thresholding Pada Segmentasi Citra Digital, Jurnal Mantik Penusa, Vol 1 No. 2 hal. 48-51, 2017.
Untari Novia Wisesty, Titik Mutiah, “Implementasi Gabor Wavelet dan Support Vector Machine pada Deteksi Polycystic Ovary (PCO) Berdasarkan Citra Ultrasonografi”, Ind. Journal on Computing, Vol. 1, Issue. 2, Sept 2016. pp. 67-82, tahun 2016.
Refbacks
- There are currently no refbacks.