… We provide a brief overview of palmprint recognition methods. Existing methods in the
literature essentially differ by the type of discrimination features they use and can be broadly …

… The features of eigenpairs are extracted by projecting new palm image into sup space
spanned by eigenpalm and applied for palmprint identification using probabilistic rough classifier. …

… (SURF) [4]; appearance-based approaches, eg, sub-space based on the EigenPalm and
principal component analysis (PCA) [5]; statistical approaches such as Gabor and wavelet [2, 5]…

… [31] proposed eigenpalm method by extracting the PCA data of palmprint. Imad et al. [32,33]
proposed a sparse representation-based method by extracting the subspace …

… Eigenpalms are formed by the training set’s vector. Co-variance matrix is formed of the …
Selected feature should be unique in whole population. For palmprint recognition features can be …

… palmprint identification framework with high generalization capability for operating on
different contactless palmprint … A biometric identification system based on eigenpalm and …

… a promising latent direction feature for palmprint recognition. In our future … features for
palmprint recognition. For example, it could be interesting to exploit the latent direction features …

… PCANet can extract palmprint depth feature information without the intervention of prior … In
this paper, we use two convolutional layers to extract palmprint/palmvein features, which can …

… By visualizing the intermediate features from a CNN-based palmprint recognition model,
we … feature map into 1-dimension and excites it back. Then we train this model on palmprint …

… Researchers have also proposed a number of approaches based on coding to extract
features for palmprint recognition. These include Fourier transform, the Gaussian derivative filter, …