Palmprint recognition using eigenpalms features

Guangming Lu, Dapeng Zhang, Kuanquan Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

486 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)1463-1467
Number of pages5
JournalPattern Recognition Letters
Issue number9-10
Publication statusPublished - 1 Jun 2003


  • Eigenpalms
  • K-L transform
  • Palmprint recognition

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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