Application of two-dimensional principal component analysis for recognition of face images

Facial Feature Extraction Based on Weighted ALW and Pulse-Coupled Neural Network

“…We respectively random select 3, 4, and 5, samples in ORL face database as training set, the remaining as test set. Our algorithm is compared with the principal component analysis (PCA) [8], linear decision analysis (LDA) [9], independent component analysis (ICA) [10], M-PCNN [15] and the algorithm in literature [17]. In order to eliminate the influence of different classifier for recognition accuracy, each method is classified by support vector machine with the optimum parameters.…”

“…But it can't meet the real-time requirement because of its high computation complexity. Face image will be projected into subspace by subspace methods [8], such as principal component analysis (PCA), linear decision analysis [9][10] (LDA) and independent component analysis (ICA). The projection coefficient is considered as feature.…”