A High Performace of Local Binary Pattern on Classify Javanese Character Classification

Ajib Susanto, Daurat Sinaga, Christy Atika Sari, Eko Hari Rachmawanto, De Rosal Ignatius Moses Setiadi

Abstract


The classification of Javanese character images is done with the aim of recognizing each character. The selected classification algorithm is K-Nearest Neighbor (KNN) at K = 1, 3, 5, 7, and 9. To improve KNN performance in Javanese character written by the author, and to prove that feature extraction is needed in the process image classification of Javanese character. In this study selected Local Binary Patter (LBP) as a feature extraction because there are research objects with a certain level of slope. The LBP parameters are used between [16 16], [32 32], [64 64], [128 128], and [256 256]. Experiments were performed on 80 training drawings and 40 test images. KNN values after combination with LBP characteristic extraction were 82.5% at K = 3 and LBP parameters [64 64].

Keywords


Optical Character Recognition, Javanese Character, Local Binary Pattern

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References


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DOI: https://doi.org/10.15294/sji.v5i1.14017

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