Pengenalan Huruf Isyarat Tangan Menggunakan Ekstraksi Ciri Local Binary Pattern

  • M. Adhi Satria Universitas Telkom
  • Kurniawan Nur Ramadhani Universitas Telkom
  • Anditya Arifianto Universitas Telkom
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Abstract

Pada penelitian ini dibangun sistem pengenalan huruf isyarat tangan menggunakan metode ekstraksi ciri Local Binary Patterns (LBP). Metode LBP memiliki kehandalan dalam melakukan analisis tekstur, mengatasi penskalaan dan citra yang kabur. Untuk algoritma klasifikasi, digunakan metode k-Nearest Neighbour (KNN) dan Support Vector Machine (SVM). Parameter LBP terbaik didapatkan untuk nilai R=10 dan P=16 menggunakan SVM dengan kernel Gaussian. Performansi terbaik dalam penelitian ini didapatkan untuk nilai F1-Score 99,84%.

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Published
2018-05-23
How to Cite
Satria, M. A., Ramadhani, K. N., & Arifianto, A. (2018). Pengenalan Huruf Isyarat Tangan Menggunakan Ekstraksi Ciri Local Binary Pattern. Indonesian Journal on Computing (Indo-JC), 3(1), 75-84. https://doi.org/10.21108/INDOJC.2018.3.1.215
Section
Computer Science