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The face is one of the media to identify someone, a human face has a very high level of variability. Many methods have been introduced by researchers and scientists in recognizing one's face, one of the methods introduced is the Feature Extraction of Gray Level Co-Occurrence Matrix (GLCM) and Learning Vector Quantization (LVQ). GLCM feature extraction is used for data extraction/learning process whereas a data analysis process (face recognition, cropping and storing data) the LVQ method is used for the data training process where the data that has been processed in GLCM feature extraction which still has large dimensions are processed to be smaller dimensions. So this test uses data of 190 photos and gets a match of 90%, the authors conclude that the GLCM feature extraction and LVQ method can very well recognize faces contained in the database.
Choong Hwan Lee, J. S. (1996). Automatic Human Face Location in a Complex Background Using Motion and Color Information. Pattern Recognition , 27.
Demuth, h. a. (2002). Neural Network Toolbox User’s Guide. The MathWork .
Dewi, R. H. (2014). Identifikasi Penyakit Pada Daun Tebu Dengan Gray Level Co-occurrence Matrix dan Color Moments. Teknologi Informasi dan Ilmu Komputer (JTIIK) , 2, 70-77.
Gorodnichy, D. (2004). Introduction to the First IEEE Workshop on Face Processing in Video. Conference Publications , 27.
j. Lyons, M. B. (1999). Automatic Classification of Single Facial Images. Pattern Analysis and Machine Intelligence , 21, 1357-1362.
Kusumadewi, S. (2004). Membangun Jaringan Syaraf Tiruan Menggunakan Matlab dan Excellink.
Maheshwary, P. d. (2009). Prototype System for Retrieval of Remote Sensing Images based on Color Moment and Gray Level Co-Occurrence Matrix. IJCSI International Journal of Computer Science Issues , 3.
Muhathir. (2017). KLASIFIKASI EKSPRESI WAJAH MENGGUNAKAN BAG OF VISUAL. Journal of Informatics and Telecommunication Engineering, 1 (2), 73-82. | Google Scholar
Zhou, S. K. (2004). Probabilistic recognition of human faces from video. Computer Vision and Image Understanding. 91. 214-245.