Feature Extraction Using Statistical Moments of Wavelet Transform for Iris Recognition

被引：0

作者：

Suciati, Nanik ^{[1
]}

Anugrah, Afdhal Basith ^{[1
]}

Fatichah, Chastine ^{[1
]}

Tjandrasa, Handayani ^{[1
]}

Arifin, Agus Zainal ^{[1
]}

Purwitasari, Diana ^{[1
]}

Navastara, Dini Adni ^{[1
]}

机构：

[1] Inst Teknol Sepuluh Nopember, Dept Informat, Surabaya, Indonesia

来源：

PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON INFORMATION & COMMUNICATION TECHNOLOGY AND SYSTEMS (ICTS) | 2016年

关键词：

wavelet transform; statistical moments; support vector machine; iris recognition;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Iris is unique for each person, so that it can be used as one alternative solution for human identification. In this study, an iris recognition system is developed to automatically identify a person by using eye image data. Firstly, iris area of eye image is detected using Canny Edge Detection and Hough Transform methods. Secondly, texture feature of iris image is extracted using statistical moments of Wavelet Transform. Furthermore, the texture feature representation is recognized using Support Vector Machine classifier method. Experiment on CASIA eye image dataset gives good recognition rate, that is 93.5%.

引用

页码：193 / 198

页数：6

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