Identifikasi Citra Iris Mata Menggunakan Scale-Invariant Feature Transform (SIFT)

Prawira, Surya Putra (2019) Identifikasi Citra Iris Mata Menggunakan Scale-Invariant Feature Transform (SIFT). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Iris mata merupakan bagian tubuh yang bersifat konsisten
dan tidak mengalami perubahan terhadap umur sehingga fiturnya tetap terjaga dan bersifat unik untuk setiap orang. Dengan adanya karakteristik tersebut, iris mata menjadi objek yang ideal untuk digunakan sebagai subjek untuk mengetahui kualitas performa ScaleInvariant Feature Transform(SIFT) sebagai metode klasifikasi. Dilakukan pra-pemrosesan terhadap citra mata yang dijadikan subjek pengujian, dan hasil tersebut akan diuji menggunakan
SIFT dengan citra lainnya yang telah melalui proses yang sama. Dilakukan pengujian dalam jumlah yang dapat merepresentasikan performa SIFT dengan tepat. Data yang didapatkan di pengujian akan diolah dengan Receiver Operating Characteristic(ROC), untuk mendapatkan indeks nilai kualitas performa SIFT terhadap identifikasi iris mata. Hasil dari Receiver Operating Characteristic menunjukkan menunjukkan performa SIFT dalam identifikasi iris mata.
Eye iris is a part of the body that is sustained and does not undergo changes as the person ages, which keeps the unique features intact, and different amongst people. With that in mind, iris is a potentially ideal object to determine the identity of a subject, which can be used to test the performance of Scale-Invariant Feature Transform (SIFT) as an identifier. The eyes receives pre-processing, which is then continued by
SIFT along with other eye image which already being processed beforehand.every match will be noted with how many matching point resulted in the match. Aforementioned matching point will then be classified through Receiver Operating Characteristic (ROC), in the form of a curve. The area below the curve represents the quality of performance the SIFT has over eye identification, in the form of a value between 0 to 1. Result from Receiver Operating CHaracteristic determines the quality of SIFT performance in identifying the eye

Item Type: Thesis (Undergraduate)
Additional Information: RSE 006.42 Pra i-1 2019
Uncontrolled Keywords: Iris Mata, Scale-Invariant Feature Transform, Receiver Operating Characteristic
Subjects: T Technology > T Technology (General) > T58.5 Information technology. IT--Auditing
T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105.546 Computer algorithms
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7882.B56 Biometric identification
Divisions: Faculty of Industrial Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User: Surya Putra Prawira
Date Deposited: 28 Jun 2021 03:37
Last Modified: 28 Jun 2021 03:37

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