Skip to Main Content
The problem of face recognition using Laplacian pyramids with different orientations and independent components is addressed in this paper. The edginess like information is obtained by using Oriented Laplacian of Gaussian (OLOG) methods with four different orientations (0°, 45°, 90°, and 135°) then preprocessing is done by using Principle Component analysis (PCA) before obtaining the Independent Components. The independent components obtained by ICA algorithms are used as feature vectors for classification. The Euclidean distance (L2) classifier is used for testing of images. The algorithm is tested on two different databases of face images for variation in illumination, facial expressions and facial poses up to 180° rotation angle.