TY - GEN
T1 - Wavelet based independent component analysis for palmprint identification
AU - Lu, Guang Ming
AU - Wang, Kuan Quan
AU - Zhang, David
PY - 2004
Y1 - 2004
N2 - This paper presents a multi-resolution analysis based Independent Component Analysis (ICA) method for automatic palmprint identification. The ICA is well known by its feature representation ability recently, in which the desired representation is the one that minimizes the statistical independence of the components of the representation. Such a representation can capture the essential feature and the structure of the palmprint images. At the same time, the palmprints have a great deal of different features, such as principal lines, wrinkles, ridges, minutiae points and texture, which can be regarded as multi-scale features. Then, it is reasonable for us to integrate the multi-resolution analysis method and ICA to represent the palmprint features. The experiment results show that the integrated method is more efficient than ICA algorithm.
AB - This paper presents a multi-resolution analysis based Independent Component Analysis (ICA) method for automatic palmprint identification. The ICA is well known by its feature representation ability recently, in which the desired representation is the one that minimizes the statistical independence of the components of the representation. Such a representation can capture the essential feature and the structure of the palmprint images. At the same time, the palmprints have a great deal of different features, such as principal lines, wrinkles, ridges, minutiae points and texture, which can be regarded as multi-scale features. Then, it is reasonable for us to integrate the multi-resolution analysis method and ICA to represent the palmprint features. The experiment results show that the integrated method is more efficient than ICA algorithm.
KW - Independent Component Analysis
KW - Multi-resolution Analysis
KW - Palmprint Identification
UR - https://www.scopus.com/pages/publications/6344229781
U2 - 10.1109/ICMLC.2004.1380404
DO - 10.1109/ICMLC.2004.1380404
M3 - 会议稿件
AN - SCOPUS:6344229781
SN - 0780384032
SN - 9780780384033
T3 - Proceedings of 2004 International Conference on Machine Learning and Cybernetics
SP - 3547
EP - 3550
BT - Proceedings of 2004 International Conference on Machine Learning and Cybernetics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Machine Learning and Cybernetics, ICMLC 2004
Y2 - 26 August 2004 through 29 August 2004
ER -