Title :
Research on face and iris feature recognition based on 2DDCT and Kernel Fisher Discriminant Analysis
Author :
Gan, Jun-Ying ; Gao, Jian-hu ; Liu, Jun-feng
Author_Institution :
Sch. of Inf., Wuyi Univ., Jiangmen
Abstract :
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.
Keywords :
biometrics (access control); discrete cosine transforms; face recognition; feature extraction; image classification; image fusion; visual databases; 2D discrete cosine transform; 2DDCT; Chinese Academy of Sciences; Institute of Automation; Kernel fisher discriminant analysis; Olivetti Research Laboratory; diagonal image transform; face database; face recognition; feature compression; feature fusion; iris database; iris feature recognition; multimodal biometric identification; nearest neighbor classifier; Discrete cosine transforms; Discrete transforms; Face recognition; Image analysis; Image coding; Image databases; Iris; Kernel; Performance analysis; Spatial databases; Face Recognition; Feature Fusion; Iris Recognition; Two-Dimensional Discrete Cosine Transform;
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2008. ICWAPR '08. International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-2238-8
Electronic_ISBN :
978-1-4244-2239-5
DOI :
10.1109/ICWAPR.2008.4635812
