A new method for human ear recognition using Haar wavelet decomposition and LDA/GSVD

DOI

10.2991/icmse-18.2018.7How to use a DOI?

Keywords

haar wavelet decomposition, LDA/GSVD, human ear recognition.

Abstract

In the case of high dimension and small sample, the feature extraction method using Fisher linear discriminant analysis has a problem of pathological singularity. There are many solutions to this problem, in which LDA/GSVD algorithm overcomes the shortcomings of the existing methods, has a good recognition rate. However, the direct use of LDA/GSVD to reduce the dimension of human ear images, it still encounters the problem of large amount of calculation and slow calculation speed. So the author proposes a new method which apply wavelet decomposition on the human ear image and then use LDA/GSVD algorithm. The method is proved by experiments that it has a good recognition rate and is an effective feature extraction approach.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hailong Zhao
PY  - 2018/05
DA  - 2018/05
TI  - A new method for human ear recognition using Haar wavelet decomposition and LDA/GSVD
BT  - Proceedings of the 2018 8th International Conference on Manufacturing Science and Engineering (ICMSE 2018)
PB  - Atlantis Press
SP  - 30
EP  - 33
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-18.2018.7
DO  - 10.2991/icmse-18.2018.7
ID  - Zhao2018/05
ER  -