Using SIFT Features in Palmprint Authentication
Refereed conference paper presented and published in conference proceedings


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AbstractAs a new branch of biometrics, palmprint authentication has attracted increasing amount of attention because palmprints are abundant of line features so that low resolution images can be used In this paper, we present two novel approaches for palmprints authentication. Firstly, we employ the SIFT (Scale Invariant Feature Transformation) for palmprint authentication. Point-wise matching is used to match SIFT key points extracted form palmprint images. Secondly, we extend a time series technology, SAX (Symbolic Aggregate approximation), to 2D data for the palmprint representation and matching. Using a public palmprint database, we demonstrate that the two proposed approaches, when combined together, can achieve the palmprint authentication accuracy comparable to that of the state of the art algorithms.
All Author(s) ListChen JS, Moon YS
Name of Conference19th International Conference on Pattern Recognition (ICPR 2008)
Start Date of Conference08/12/2008
End Date of Conference11/12/2008
Place of ConferenceTampa
Country/Region of ConferenceUnited States of America
Detailed descriptionorganized by IAPR,
Year2008
Month1
Day1
PublisherIEEE
Pages2853 - 2856
ISBN978-1-4244-2174-9
ISSN1051-4651
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesComputer Science; Computer Science, Artificial Intelligence

Last updated on 2020-26-10 at 00:43