Matches in SemOpenAlex for { <https://semopenalex.org/work/W2034114524> ?p ?o ?g. }
- W2034114524 endingPage "37" @default.
- W2034114524 startingPage "1" @default.
- W2034114524 abstract "Palmprint images contain rich unique features for reliable human identification, which makes it a very competitive topic in biometric research. A great many different low resolution palmprint recognition algorithms have been developed, which can be roughly grouped into three categories: holistic-based, feature-based, and hybrid methods. The purpose of this article is to provide an updated survey of palmprint recognition methods, and present a comparative study to evaluate the performance of the state-of-the-art palmprint recognition methods. Using the Hong Kong Polytechnic University (HKPU) palmprint database (version 2), we compare the recognition performance of a number of holistic-based (Fisherpalms and DCT+LDA) and local feature-based (competitive code, ordinal code, robust line orientation code, derivative of Gaussian code, and wide line detector) methods, and then investigate the error correlation and score-level fusion performance of different algorithms. After discussing the achievements and limitations of current palmprint recognition algorithms, we conclude with providing several potential research directions for the future." @default.
- W2034114524 created "2016-06-24" @default.
- W2034114524 creator A5004565086 @default.
- W2034114524 creator A5018318136 @default.
- W2034114524 creator A5020069410 @default.
- W2034114524 date "2012-01-01" @default.
- W2034114524 modified "2023-10-10" @default.
- W2034114524 title "A Comparative Study of Palmprint Recognition Algorithms" @default.
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