Three-directional of the ID-diagonal fisherface modeling based feature extraction
Arif Muntasa, Indah Agustien Siradjuddin, Rima Tri Wahyuningrum · 2016
Three directional of the 1D diagonal fisherface for feature extraction is proposed in this research for the face recognition system. Three directional of the diagonal matrix is built in the proposed method, i.e. the input face image is transformed into a diagonal matrix. Therefore, another form of the input image is created for the feature extraction using the diagonal matrix of the input image. The diagonal matrix is then transformed into 1D matrix for each training set. The feature extraction used this matrix to create the projection and weight matrix using Fisher Face. Two until ten features are extracted using the proposed method. There are four distance methods are used in the experiments, i.e. Euclidian, Manhattan, Canberra, and Chebychev. The experiments of the proposed system are conducted on three databases, i.e. ORL, University of Bern, and YALE-A databases. The recognition accuracy of the proposed model for face recognition achieved up to 92% accuracy.