Pengenalan Iris Menggunakan Ekstraksi Fitur Average Absolute Deviation dan Gray-Level Co-Occurrence Matrix

Laily, Rahma Dini Maghfirotul (2018) Pengenalan Iris Menggunakan Ekstraksi Fitur Average Absolute Deviation dan Gray-Level Co-Occurrence Matrix. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pengenalan iris mata adalah teknik pengenalan pola yang digunakan dalam aplikasi biometrik. Teknik biometrik ini menghasilkan pola acak yang unik secara statistik. Dengan kata lain, tekstur iris mata adalah bagian yang unik dimiliki pada masing-masing orang. Dalam Tugas Akhir ini diimplementasikan pengenalan iris menggunakan metode ekstraksi fitur Gray-Level Cooccurrence Matrix (GLCM) dan metode ekstraksi fitur Average Absolute Deviation (AAD). Metode klasifikasi yang dipakai adalah Artificial Neural Network (ANN). Sebelum dilakukan ekstraksi fitur, terlebih dahulu dilakukan preprocessing untuk identifikasi dan normalisasi bagian iris mata. Uji coba yang dilakukan menggunakan dataset mata CASIA versi 1.0. Hasil uji coba yang menggunakan metode ekstraksi fitur GLCM dan AAD dengan klasifikasi ANN mendapatkan akurasi terbaik sebesar 89.23%. ================= Iris recognition is a pattern recognition technique used in biometric applications. This biometric technique generates a unique random pattern statistically. In other words, the texture of the iris is the part that is unique to each person. This final project implements feature extraction methods Gray-Level Cooccurrence Matrix (GLCM) and Average Absolute Deviation (AAD for iris recognition. The classification method used is Artificial Neural Netrowk (ANN). Before features extraction, first performed preprocessing for identification and normalization of the iris. Trials performed using CASIA version 1.0 eye datasets. The test results using GLCM and AAD feature extraction methods with ANN classification obtained the best accuracy of 89.23%.

Item Type: Thesis (Undergraduate)
Additional Information: RSIf 006.4 Lai p
Uncontrolled Keywords: pengenalan iris, average absolute deviation, gray-level co-occurrence matrix, artificial neural network, Iris Recognition, Average Absolute Deviation, Gray-Level Cooccurrence Matrix, Artificial Neural Network
Subjects: T Technology > T Technology (General)
T Technology > T Technology (General) > T57.5 Data Processing
T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques
Divisions: Faculty of Information and Communication Technology > Informatics > (S1) Undergraduate Theses
Depositing User: Rahma Dini Maghfirotul Laily
Date Deposited: 28 Dec 2018 07:05
Last Modified: 28 Dec 2018 07:05
URI: http://repository.its.ac.id/id/eprint/53401

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