DocumentCode
3585988
Title
Bit-planes decomposition with eigenpalm on different distance measures
Author
Lee, Therry Z. ; Bong, David B. L.
Author_Institution
Fac. of Eng., Univ. Malaysia Sarawak, Kota Samarahan, Malaysia
fYear
2014
Firstpage
137
Lastpage
140
Abstract
In this paper, a palmprint recognition using bitplane extraction with Principal Component Analysis is presented. Different distance measures are applied for classification to evaluate the recognition performance. Also, bit-plane is selected by analyzing the principal components. Hong Kong PolyU Palmprint Database is applied in this paper. The result showed that the palmprint recognition can achieved 90.42% performance rate by using approximately 4.17% of total principal components by using Manhattan Distance.
Keywords
feature extraction; palmprint recognition; principal component analysis; Hong Kong PolyU Palmprint Database; Manhattan distance; bit-plane decomposition; bitplane extraction; distance measure; eigenpalm; palmprint recognition; principal component analysis; recognition performance; Databases; Eigenvalues and eigenfunctions; Face recognition; Feature extraction; Principal component analysis; Testing; Training; PCA; Palmprint recognition; bit-planes; distance measures;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Process and Control (ICSPC), 2014 IEEE Conference on
Print_ISBN
978-1-4799-6105-4
Type
conf
DOI
10.1109/SPC.2014.7086245
Filename
7086245
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