Rekognisi Wajah Pada Sistem Smart Class Untuk Deteksi Kehadiran Mahasiswa Menggunakan Metode Viola Jones dan Local Binary Patterns Histograms (LBPH) Berbasis Raspberry Pi - Fitrahadi Surya Dharma; Fitri Utaminingrum; Rizal Maulana (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Facial recognition is one of the techniques in computer vision that is able to recognize a person's face from an image. The application of face recognition into the presence system is very important considering that there are still cases of attendance data manipulation by students in the presence system using manual - filling signatures on the attendance sheet. Lack of tight supervision in filling attendance sheets is an event that is vulnerable to cases of manipulating attendance data. Therefore in this study try to present a presence system that uses images to find out the presence of students. The trick is to take pictures using a camera that is placed in front of the class, just above the blackboard facing the student. From the images taken, the system will then detect the faces of students using the Viola Jones method of the OpenCV library combined with YCbCr skin color pixel detection to avoid false detection. And for face recognition students will be using the local binary patterns histograms method from the OpenCV library. Accuracy results obtained by the system showed the level of detection accuracy of 82.33% and recognition accuracy of 50.83% in the morning, 61.11% during the day, and 58.89% at night. The average total computing time for the detection of one student is 0.293 seconds, two students 0.297 seconds, three students 0.317 seconds, four students 0.313 seconds, five students 0.31 seconds and six students 0.307 seconds. While the average total face recognition computing time for one student is 2.17 seconds, two students 2.58 seconds, three students 3.01 seconds, four students 3.38 seconds, five students 3.78 seconds, and six students 4 .12 seconds.