Iris recognition using combined support vector machine and Hamming distance approach

作者：

Highlights：

• A combination of SVM & Hamming distance approach is used for iris recognition.

• The proposed method has a recognition rate of 99.91% & 99.88% on CASIA & Chek image database.

• The accuracy is excellent for the CASIA & Chek image database in terms of FAR & FRR.

摘要

•A combination of SVM & Hamming distance approach is used for iris recognition.•The proposed method has a recognition rate of 99.91% & 99.88% on CASIA & Chek image database.•The accuracy is excellent for the CASIA & Chek image database in terms of FAR & FRR.

论文关键词：Iris recognition,Noise removal,Support vector machine,Hamming distance,Zigzag collarette area

论文评审过程：Available online 9 August 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.07.083