On-line signature verification based on PCA (Principal Component Analysis) and MCA (Minor Component Analysis)

Bin Li, Kuanquan Wang, Dapeng Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)

Abstract

On-line signature verification is still an active topic in the field of biometrics. This paper proposes a novel method based on PCA (Principal Component Analysis) and MCA (Minor Component Analysis). Different from the application of PCA in other fields, both principal and minor components are used to signature verification, and MC plays a very important role. Comparing with DTW and the discriminance of Euclidean distance, the method based on PCA and MCA is better. With 1215 signatures contributed by 81 signers of which numbers of reference signatures, genuine signatures and forgeries (skilled) are 5 respectively, the EER is about 5%.
Original languageEnglish
Pages (from-to)540-546
Number of pages7
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3072
Publication statusPublished - 1 Dec 2004

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this