Fuzzy Normalisation Methods for Pattern Verification

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

2 Citations (Scopus)


A fuzzy approach to normalisation methods for pattern verification is presented in this paper. For an input token and a claimed identity, a score is calculated and compared with a given threshold to accept or reject the claimed person. The score is regarded as a fuzzy memebership function in this approach. The paper shows how to find effective scores to reduce both false rejection and false acceptance errors. Speaker verification experiments performed on the ANDOSL database and utterance verification experiments performed on the TI46 database showed better results for fuzzy methods
Original languageEnglish
Title of host publicationInternational Conference on Biometric Authentication, ICBA 2004
EditorsD Zhang, AK Jain
Place of PublicationBerlin Heidelberg, Germany.
Number of pages7
ISBN (Print)9783540221463
Publication statusPublished - 2004
EventInternational Conference on Biometric Authentication - , Hong Kong
Duration: 15 Jul 200417 Jul 2004


ConferenceInternational Conference on Biometric Authentication
Country/TerritoryHong Kong


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