… traits that is the KFA (Kernel Fisher Analysis) that consists of the application of the LDA (Linear
Discriminant Analysis) on the PCA (Principal Components Analysis) space. The main …

… (knuckle prints) are extracted with using analytical processing. Afterwards, the patterns of
knuckle prints … , then by using nonlinear Kernel Fisher Discriminant method most discriminative …

… analysis (MMDA) method for FKP matching based on graph embedded learning under the
Fisher discriminant analysis … Equally, H can be expressed by the convolution kernel in the …

… , summary of inner- and dorsal-knuckle print recognition, … finger knuckle joints consist of
highly rich lines and creases known as finger-dorsal- or finger-back-surface-based knuckle prints…

… ), ICA (Independent Component Analysis) [1], OLDA (Orthogonal Linear Discriminent
Analysis) [2], KPCA (Kernel Principal Analysis) [3], and also Fisher Analysis which consists of the …

… by using KPCA (kernel principal component analysis) algorithm. Then Linear Descriminant
… authentication using finger knuckle print as biometric trait is presented in this section. …

… WLE combines Fisher criterion with manifold learning … principal components analysis (PCA),
LDA and LDE. … A method to select the parameter of Gaussian kernel is put forward. …

… The biometric finger knuckle print (FKP) is employed for … To reduce dimension, kernel
principal component analysis … Fisher in 1936 and is meant for two-dimensional and later for …

… However, the subspace analysis method used in the feature … In this scheme, a Fisher
vector in a convolutional neural … to which a kernel is defined as named K. The values of this …

… -based biometrics modality (Finger-Knuckle-Print, FKP) has attracted … the knuckle lines and
the textures in the outer finger surface. … identification based on single knuckle print image. In …