Fauzi, Hilman and Erika, Cynthia and Sa’idah, Sofia and Oscandar, Fahmi (2022) Classification of Gender Individual Identification using Local Binary Pattern on Palatine rugae Image. Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), 8 (3). pp. 422-430.
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Abstract
Major disasters caused many casualties with the condition of the damaged bodies. It causes the individual identification process to be ineffective through biometric characteristics (such as lips and fingerprint). However, the palatine rugae can carry the individual identification process. Palatine rugae have unique and individual characteristics and are more resistant to trauma because of their internal location. In this study, an individual identification system is proposed to identify gender using the image of palatine rugae. The proposed system is developed by several algorithms and methods such as Local Binary Pattern (LBP) as the feature extraction method and K-Nearest Neighbor (KNN) as the classification method. Based on the result of the system performed test, the proposed system can identify the gender of an individual by the combination of recognized palatine rugae patterns. The system achieved an accuracy test result of 100% with a specific configuration of LBP and KNN. The research contribution in this study is to develop the individual gender identification system, which proceed with the palatine rugae pattern image with unique biometric characteristic as an input. The system applied several methods and algorithms such as Geometric Active Contour (GAC) as segmentation algorithm, Local Binary Pattern (LBP) as feature extraction method, and K Nearest Neighbor (KNN) as classification method.
| Item Type: | Artikel Umum |
|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisi / Prodi: | Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Electrical Engineering (S1-Teknik Elektro) |
| Depositing User: | M.Eng. Alfian Ma'arif |
| Date Deposited: | 07 Feb 2023 01:48 |
| Last Modified: | 07 Feb 2023 01:48 |
| URI: | http://eprints.uad.ac.id/id/eprint/39403 |
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