Iris Recognition Untuk Deteksi Mata Dengan Metode K-Nearest Neighbor
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Institusion
Politeknik Negeri Jember
Author
Anwar, Moh. Khairul
Subject
458 - Teknik Informatika
Datestamp
2022-07-26 01:07:25
Abstract :
The iris of the eye is a ring-shaped webbed part of the eye that is limited by the pupil and sclera, this iris is one of the unique organs that can distinguish each person, to recognize the fibers in the iris of the eye can use biometric recognition which is used to recognize the natural characteristics possessed This application applies computer vision where the computer is given knowledge so that it can carry out the image identification process. The method used in this study uses K-Nearest Neighbor (KNN) and Circle Hough Transform with parameters Area, Perimeter, Centroid, metric and Eccentricity The amount of testing data used in this study is 90 test data, consisting of 45 people with 1 image. right eye and 1 left eye image. that from 10 iris images tested, 6 iris images are correct and 4 iris images are false. Using the K-Nearest Neighbor classification method, the iris image can be classified with an accuracy of 60%.
The iris of the eye is a ring-shaped webbed part of the eye that is limited by the pupil and sclera, this iris is one of the unique organs that can distinguish each person, to recognize the fibers in the iris of the eye can use biometric recognition which is used to recognize the natural characteristics possessed This application applies computer vision where the computer is given knowledge so that it can carry out the image identification process. The method used in this study uses K-Nearest Neighbor (KNN) and Circle Hough Transform with parameters Area, Perimeter, Centroid, metric and Eccentricity The amount of testing data used in this study is 90 test data, consisting of 45 people with 1 image. right eye and 1 left eye image. that from 10 iris images tested, 6 iris images are correct and 4 iris images are false. Using the K-Nearest Neighbor classification method, the iris image can be classified with an accuracy of 60%.
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