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
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;
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
DOI :
10.1109/ICMLA.2011.169