Skripsi

SISTEM KEAMANAN BERBASIS CNN MENGGUNAKAN IRIS MATA YANG DINORMALISASI DENGAN DAUGMAN RUBBER SHEET MODEL

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Penilaian

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The eye iris is a biometric that has a pattern that requires high accuracy to be identified. Problems that occur are generally image quality, because if the quality of the image used is not good, such as low resolution, blurring, or unusual luster, it will cause difficulty in distinguishing between the iris and pupil. Therefore, the Daugman Rubber Sheet Model method was used to increase the accuracy of the identification results. The Daugman Rubber Sheet method is also popular among researchers who discuss the identification of the iris. The data used in this study used primary data as many as 14 individuals and secondary data as many as 44 individuals. The CNN architectural models used are VGG16, ResNet50, ResNet101, MobileNetV2, MobileNetV3, DenseNet121, DenseNet169, and IrisNet. From the classification results in the study, the Daugman Rubber Sheet Model method has a good effect on improving the classification of the iris image. However, the results were not significantly different with the non-normalized iris. It can be seen from the comparison of the results of the classification of normalized and non-normalized data, which have almost the same high accuracy with a difference of about 1%. The best CNN architectural models used are DenseNet, ResNet, and IrisNet because they have the best performance for identifying the iris with an accuracy of 99%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2207000322	T63880	T638802022	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T638802022

Publisher

Indralaya : Prodi Teknik Elektro, Fakultas Teknik Universitas Sriwijaya ;., 2022

Collation

xiii, 45 hlm.: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

621.370 7

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Teknik elektro
Teknik Sekuriti, Perekam Suara dan Topik Terkait
Sistem keamanan Iris Mata

Specific Detail Info

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Statement of Responsibility

MURZ

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