DocumentCode
3269364
Title
An Iris Recognition Approach based on Fuzzy Support Vector Machine
Author
Gu, Hongying ; Gao, Zhiwen ; Yang, Cheng
Author_Institution
Inst. of Artificial Intell., Zhejiang Univ., Hangzhou, China
Volume
2
fYear
2011
fDate
18-21 Dec. 2011
Firstpage
370
Lastpage
373
Abstract
An iris recognition system named IrisPassport is presented in this paper. Standard Deviation is used to localize the irises from iris images. After localization, IrisPassport uses Steerable Pyramid and Variant Fractal Dimension as features with orientation information. Aiming to build a robust solution for non-cooperative iris images, we adopt fuzzy support vector machine (FSVM) because we consider different samples contributes to classification differently and a member function can be used when unclassifiable regions appear. Experimental data demonstrates the potential of our new approach, and shows that it performs favorably when compared with the former algorithms.
Keywords
fuzzy set theory; iris recognition; support vector machines; IrisPassport; SVM; fuzzy support vector machine; iris recognition approach; member function; noncooperative iris images; orientation information; standard deviation; steerable pyramid dimension; variant fractal dimension; Educational institutions; Fractals; Image databases; Iris; Iris recognition; Support vector machines; Training; fuzzy support vector machine; iris recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
Conference_Location
Honolulu, HI
Print_ISBN
978-1-4577-2134-2
Type
conf
DOI
10.1109/ICMLA.2011.169
Filename
6147708
Link To Document