Subband Selection in Wavelet Packet Decomposition for Face Recognition

被引：0
|
作者：
Radji, Nadjet [1 ]
Cherifi, Dalila [1 ]
Azrar, Arab [1 ]
机构：
[1] Univ Boumerdes, Inst Elect & Elect Engn, Boumerdes, Algeria
来源：
14TH INTERNATIONAL CONFERENCE ON SCIENCES AND TECHNIQUES OF AUTOMATIC CONTROL & COMPUTER ENGINEERING STA 2013 | 2013年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we evaluated the performance of face recognition based on Wavelet Packet Decomposition (WPD) and Principal Component Analysis (PCA) at second level of decomposition where six wavelet families are employed namely: Daubechies, Haar, Coiflets, Symlets, Biorthogonal, and Reverse Biorthogonal. Firstly by taking all of the sixteen subbands obtained after the second level of decomposition and combine them using mean and product rules. Then, each subband is run separately with the purpose of selecting among them the ones that provide lowest Equal Error Rate (EER). After that, subbands with lowest EER are combined together using mean and product rules; aiming for dimensionality reduction of the input image as well as increase the performance of the recognition system.
引用
收藏
页码：494 / 500
页数：7
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