.png){kind=icon}
Return
Palmprint recognition using eigenpalms features
.png){kind=icon}
PRE
AI
DOI：10.1016/S0167-8655(02)00386-0.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, we propose a palmprint recognition method based on eigenspace technology. By means of the Karhunen-Loeve transform, the original palmprint images are transformed into a small set of feature space, called eigenpalms, which are the eigenvectors of the training set and can represent the principle components of the palmprints quite well. Then, the eigenpalm features are extracted by projecting a new palmprint image into the subspace spanned by the eigenpalms, and applied to palmprint recognition with a Euclidean distance classifier. Experimental results illustrate the effectiveness of our method in terms of the recognition rate. (C) 2002 Elsevier Science B.V. All rights reserved.
Keywords:
K-L transform
Eigenpalms
palmprint recognition
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.3
Papers:
8.0K
Citations:
1.6W
Organization
No organization information available
Cited Papers
Multimodal imaging reveals a unique autofluorescence signature of Randall’s plaque.png)
Urolithiasis
OAAI
UrolithiasisIF0
OAAIShareSaveTwo novel characteristics in palmprint verification: datum point invariance and line feature matchingPATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
ShareSaveShareSaveShareSaveShareSave no more
no more