Pengenalan Wajah dengan Pose Unik menggunakan Metode Learning Vector Quantization - Achmad Dinda Basofi Sudirman; Yuita Arum Sari; Fitri Utaminingrum (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
The face is one of the characteristics of human natural physiology that can be used for biometric identification for facial recognition. Face recognition is an alternative to systems such as presence and authentication. Nowadays there are so many companies or researchers to create a system that can recognize people's faces, but there is still a face recognition system that can be tricked by showing people who have been recognized by the system in the system's camera area, even though people who are actually recognized by the system are not in the area that. This research will utilize the LVQ method for classification or facial recognition because it is well proven in face recognition conducted by previous research. Feature extraction is used in the form of skin image taking with HSV color space because HSV color space is better at detecting skin images according to existing research. The unique face image or pose used consists of 3 different eye poses to improve the safety of face recognition. In 10 different test scenarios, the results of this study have an average accuracy of 81.3%. However, the system still cannot distinguish each pose from the existing data.