Hierarchical palmprint identification via multiple feature extraction

By J. You, Wenxin Li, David Dapeng Zhang. Pattern Recognition, 2002

311 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/3c4a86e8923996b346e87fb883a4de0dc65db6be

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In Computer Vision and Pattern Recognition

In Signal Processing

Citations in the corpus

Fisherpalms based palmprint recognition (2003, background): “, 2002) or the hybrid of these two types of features (You et al., 2002).”
An automated palmprint recognition system (2005, methodology): “Keywords: Biometric; Palmprint recognition; Palmprint pre-processing; Subspace projection methods; Similarity matching”
A biometric identification system based on eigenpalm and eigenfinger features (2005, background): “The physical characteristics of an individual that can be used in biometric identification/verification systems are fingerprint [3], [4], hand geometry [5], [6], palm print [7], [8], [9], face [4], [10], iris [11], [12], retina [13], and ear [14]; the behavioral characteristics are signature [2],…”
Personal Verification Using Palmprint and Hand Geometry Biometric (2003, methodology): “Therefore , analysis of palmprint images using Gabor filters [3], wavelets [4], Fourier transform [5], and local texture energy [6] has been proposed in the literature.”
Online Palmprint Identification (2003, background): “In the past few years, some researchers have worked on offline palmprint images and have obtained useful results [3], [4], [5], [6], [7], [9].”
Biometric verification using thermal images of palm-dorsa vein patterns (2004, methodology): “[7] applied the texture energy of palmprint for coarse-level identification.”
Palmprint feature extraction using 2-D Gabor filters (2003, background): “Research on o -line palmprint authentication has been the main focus in the past few years [1,5,22,23], where all palmprint samples are inked on paper, then transmitted into a computer through a digital scanner.”
Palmprint recognition using eigenpalms features (2003, methodology): “An average recognition rate 91% was achieved by the technology proposed in (You et al., 2002), which involved a hierarchical palmprint recognition fashion.”