Comparing the legendre wavelet filter and the gabor wavelet filter for feature extraction based on iris recognition system
Iris recognition system is today among the most reliable form of biometric recognition. Some of the reasons why the iris recognition system is reliable include; Iris never changes due to ageing and individual can be recognized with their irises from long distances up to 50m away. The iris recogn...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/4256/1/KP%202020%20%2886%29.pdf |
| _version_ | 1796868985815302144 |
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| author | Danlami, Muktar Jamel, Sapiee Ramli, Sofia Najwa Megat Azahari, Siti Radhiah |
| author_facet | Danlami, Muktar Jamel, Sapiee Ramli, Sofia Najwa Megat Azahari, Siti Radhiah |
| author_sort | Danlami, Muktar |
| collection | UTHM |
| description | Iris recognition system is today among the most
reliable form of biometric recognition. Some of the reasons why
the iris recognition system is reliable include; Iris never changes
due to ageing and individual can be recognized with their irises
from long distances up to 50m away. The iris recognition system
process includes four main steps. The four main steps are; iris
image acquisition, preprocessing, feature extraction and
matching, which makes the processes in recognizing an
individual with his or her iris. However, most researchers
recognized feature extraction as a critical stage in the
recognition process. The stage is tasked with extracting unique
feature of the individual to be recognized. Different algorithm
over two-decade has been proposed to extract features from the
iris. This research considered the Gabor filter, which is one of
the most used and Legendre wavelet filters. We also apply them
on three different datasets; CASIA, UBIRIS and MMU
databases. Then we evaluate and compare based on the False
Acceptance Rate (FAR), False Rejection Rate (FRR), Genuine
Acceptance Rate (GAR) and their accuracy. The result shows a
significate increase in recognition accuracy of the Legendre
wavelet filter against the Gabor filter with up to 5.4% difference
when applied with the UBIRIS database. |
| first_indexed | 2024-03-05T21:48:03Z |
| format | Conference or Workshop Item |
| id | uthm.eprints-4256 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:48:03Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | uthm.eprints-42562022-01-23T07:32:42Z http://eprints.uthm.edu.my/4256/ Comparing the legendre wavelet filter and the gabor wavelet filter for feature extraction based on iris recognition system Danlami, Muktar Jamel, Sapiee Ramli, Sofia Najwa Megat Azahari, Siti Radhiah T Technology (General) TA1501-1820 Applied optics. Photonics Iris recognition system is today among the most reliable form of biometric recognition. Some of the reasons why the iris recognition system is reliable include; Iris never changes due to ageing and individual can be recognized with their irises from long distances up to 50m away. The iris recognition system process includes four main steps. The four main steps are; iris image acquisition, preprocessing, feature extraction and matching, which makes the processes in recognizing an individual with his or her iris. However, most researchers recognized feature extraction as a critical stage in the recognition process. The stage is tasked with extracting unique feature of the individual to be recognized. Different algorithm over two-decade has been proposed to extract features from the iris. This research considered the Gabor filter, which is one of the most used and Legendre wavelet filters. We also apply them on three different datasets; CASIA, UBIRIS and MMU databases. Then we evaluate and compare based on the False Acceptance Rate (FAR), False Rejection Rate (FRR), Genuine Acceptance Rate (GAR) and their accuracy. The result shows a significate increase in recognition accuracy of the Legendre wavelet filter against the Gabor filter with up to 5.4% difference when applied with the UBIRIS database. 2020 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/4256/1/KP%202020%20%2886%29.pdf Danlami, Muktar and Jamel, Sapiee and Ramli, Sofia Najwa and Megat Azahari, Siti Radhiah (2020) Comparing the legendre wavelet filter and the gabor wavelet filter for feature extraction based on iris recognition system. In: 2020 IEEE 6th International Conference on Optimization and Applications (ICOA), 20-21 April 2020, Beni Mellal, Morocco. http://10.1109/ICOA49421.2020.9094465 |
| spellingShingle | T Technology (General) TA1501-1820 Applied optics. Photonics Danlami, Muktar Jamel, Sapiee Ramli, Sofia Najwa Megat Azahari, Siti Radhiah Comparing the legendre wavelet filter and the gabor wavelet filter for feature extraction based on iris recognition system |
| title | Comparing the legendre wavelet filter and the
gabor wavelet filter for feature extraction based
on iris recognition system |
| title_full | Comparing the legendre wavelet filter and the
gabor wavelet filter for feature extraction based
on iris recognition system |
| title_fullStr | Comparing the legendre wavelet filter and the
gabor wavelet filter for feature extraction based
on iris recognition system |
| title_full_unstemmed | Comparing the legendre wavelet filter and the
gabor wavelet filter for feature extraction based
on iris recognition system |
| title_short | Comparing the legendre wavelet filter and the
gabor wavelet filter for feature extraction based
on iris recognition system |
| title_sort | comparing the legendre wavelet filter and the gabor wavelet filter for feature extraction based on iris recognition system |
| topic | T Technology (General) TA1501-1820 Applied optics. Photonics |
| url | http://eprints.uthm.edu.my/4256/1/KP%202020%20%2886%29.pdf |
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