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
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;
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
DOI :
10.1109/ICOSP.2006.345932
