Pengenalan ekspresi wajah menggunakan metode fisherface dengan pendekatan jaringan syaraf tiruan backpropagation - ABIDIN, Zaenal ([Yogyakarta] : Universitas Gadjah Mada, 2010)
In daily lives, especially in interpersonal communication, face often used for expression. Facial expressions give information about the emotional state of the person. A facial expression is one of the behavioral characteristics. The components of a basic facial expression analysis system are face detection, face data extraction, and facial expression recognition. Fisherface method with backpropagation artificial neural network approach can be used for facial expression recognition. This method consists of two-stage process, namely PCA and LDA. PCA is used to reduce the dimension, while the LDA is used to features extraction of facial expressions. The system was tested with 2 databases namely JAFFE database and MUG database. The system correctly classified the expression in 86.85%, and false positive 25 for image type I of JAFFE, image type II of JAFFE correctly classified the expression in 89.20% and false positive 15, meanwhile image type III of JAFFE correctly classified the expression in 87.79%, and false positive 16. The image of MUG correctly classified the expression in 98.09%, and false positive 5.