DocumentCode
1945601
Title
Kernel-based Classifier for Iris Recognition
Author
Shao, Shuai ; Xie, Mei
Author_Institution
Inst. of Electr. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu
Volume
4
fYear
2006
fDate
16-20 Nov. 2006
Abstract
Kernel-based nonlinear feature extraction and classification algorithms are a popular new research direction in machine learning and widely used in many fields. Firstly, we will give an overview of kernel Fisher discriminant analysis and support vector machine, and then the description of multi-class classification method applied for them. The performance of these two classification method is analyzed on CASIA II database
Keywords
biometrics (access control); feature extraction; image classification; learning (artificial intelligence); support vector machines; CASIA II database; iris recognition; kernel Fisher discriminant analysis; kernel-based classifier; kernel-based nonlinear feature extraction; machine learning; multiclass classification method; support vector machine; Classification algorithms; Databases; Feature extraction; Iris recognition; Kernel; Machine learning; Machine learning algorithms; Performance analysis; Support vector machine classification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 2006 8th International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9736-3
Electronic_ISBN
0-7803-9736-3
Type
conf
DOI
10.1109/ICOSP.2006.345932
Filename
4129624
Link To Document