Iris Segmentation using Gradient Magnitude and Fourier Descriptor for Multimodal Biometric Authentication System
| Main Authors: | Sulaeman, Defiana; Department of Information Technology, Swiss German University, Edutown BSD City, Tangerang 15339, Nugroho, Anto Satriyo; Center for Information and Communication Technology Agency for Assessment & Application of Technology (PTIK-BPPT) Teknologi 3 Bld., 2F, Puspitek Serpong, Tangerang Selatan, Galinium, Maulahikmah; Department of Information Technology, Swiss German University, Edutown BSD City, Tangerang 15339 |
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| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
ITB Journal Publisher, LPPM ITB
, 2016
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| Subjects: | |
| Online Access: |
http://journals.itb.ac.id/index.php/jictra/article/view/1542 http://journals.itb.ac.id/index.php/jictra/article/view/1542/1801 |
Daftar Isi:
- Perfectly segmenting the area of the iris is one of the most important steps in iris recognition. There are several problematic areas that affect the accuracy of the iris segmentation step, such as eyelids, eyelashes, glasses, pupil (due to less accurate iris segmentation), motion blur, and lighting and specular reflections. To solve these problems, gradient magnitude and Fourier descriptor are employed to do iris segmentation in the proposed Multimodal Biometric Authentication System (MBAS). This approach showed quite promising results, i.e. an accuracy rate of 97%. The result of the iris recognition system was combined with the result of an open-source fingerprint recognition system to develop a multimodal biometrics authentication system. The results of the fusion between iris and fingerprint authentication were 99% accurate. Data from Multimedia Malaysia University (MMUI) and our own prepared database, the SGU-MB-1 dataset, were used to test the accuracy of the proposed system.