RESEARCH ON FACE AND IRIS FEATURE RECOGNITION BASED ON 2DDCT AND KERNEL FISHER DISCRIMINANT ANALYSIS

被引：3
|
作者：
Gan, Jun-Ying [1 ]
Gao, Jian-Hu [1 ]
Liu, Jun-Feng [1 ]
机构：
[1] Wuyi Univ, Sch Informat, Jiangmen 529020, Guangdong, Peoples R China
来源：
PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION, VOLS 1 AND 2 | 2008年
关键词：
Two-Dimensional Discrete Cosine Transform; Face Recognition; Iris Recognition; Feature Fusion;
D O I：
10.1109/ICWAPR.2008.4635812
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Combined with diagonal image transform, two-dimensional discrete cosine transform (2DDCT) is used in face and iris image for feature compression; then Kernel Fisher Discriminant Analysis (KFDA) is chosen as feature fusion; finally, Nearest Neighbor (NN) classifier is selected to perform recognition. Experimental results on ORL (Olivetti Research Laboratory) face database and CASIA (Chinese Academy of Sciences, Institute of Automation) iris database show that the dimension is reduced, the classified information is utilized, and correct recognition rate is improved effectively. A new approach is supplied for multimodal biometric identification.
引用
收藏
页码：401 / 405
页数：5
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