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

Ajib Susanto(1), Daurat Sinaga(2), Christy Atika Sari(3), Eko Hari Rachmawanto(4), De Rosal Ignatius Moses Setiadi(5),

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


(1) Teknik Informatika Universitas Dian Nuswantoro Semarang
(2) Teknik Informatika Universitas Dian Nuswantoro Semarang
(3) Teknik Informatika Universitas Dian Nuswantoro Semarang
(4) Teknik Informatika Universitas Dian Nuswantoro Semarang
(5) Teknik Informatika Universitas Dian Nuswantoro Semarang

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

Full Text:

PDF

References

González, A., Bergasa, L. M., Yebes, J. J., & Bronte, S. (2012, November). A character recognition method in natural scene images. In Pattern Recognition (ICPR), 2012 21st International Conference on (pp. 621-624). IEEE.

Yadav, D., Sánchez-Cuadrado, S., & Morato, J. (2013). Optical character recognition for Hindi language using a neural-network approach. JIPS, 9(1), 117-140.

Misnadin, R. A., Mola, S. A., & Fanggidae, A. (2016). Pengenalan Pola Tulisan Tangan dengan Metode K–Nearest Neighbor. Jurnal Komputer dan Informatika (JICON), 2(1), 65-72.

Fikri, R., Arnia, F., & Muharar, R. (2016). Pengenalan Karakter Tulisan Tangan Jawi Menggunakan Metode New Relative Context dan SVM. Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI), 5(3), 1-6.

Munggaran, L. C., Nuryuliani, N., & Choyrivanie, U. (2010) Klasiï¬kasi Karakter Tulisan Tangan berdasarkan Pola Segmen. Jurnal Ilmiah Program Ilmu Komputer.

Singh, G., & Lehri, S. (2012). Recognition of Handwritten Hindi Characters using Backpropagation Neural Network. International Journal of Computer Science and Information Technologies, 3(4), 4892-4895.

I. B. Kusuma & A. Kartika. (2017). Image Spoofing Detection Using Local Binary Pattern. J. Masy. Inform. Indones. 2(1), 49–54.

Hau, C. C. (Ed.). (2015). Handbook of pattern recognition and computer vision. World Scientific.

Akbar, R., & Sarwoko, E. A. (2016). Studi Analisis Pengenalan Pola Tulisan Tangan Angka Arabic (Indian) menggunakan Metode K-Nearest Neighbors dan Connected Component Labeling. Dinamika Rekayasa, 12(2), 45-51.

Indriani, O. R., Kusuma, E. J., Sari, C. A., & Rachmawanto, E. H. (2017, November). Tomatoes classification using K-NN based on GLCM and HSV color space. In Innovative and Creative Information Technology (ICITech), 2017 International Conference on (pp. 1-6). IEEE.

Abdullah, S., Huda, S. N., Bohani, F. A., Nayef, B. H., Sahran, S., Al Akash, O., ... & Ismail, F. (2016). Round Randomized Learning Vector Quantization for Brain Tumor Imaging. Computational and mathematical methods in medicine, 2016.

Syam, R. M. (2013). Pengenalan Aksara Jawa Tulisan Tangan dengan Menggunakan Ekstraksi Fitur Zoning dan Klasifikasi K-Nearest Neighbour.

Refbacks

  • There are currently no refbacks.


Bookmark and Share


Scientific Journal of Informatics (SJI)
p-ISSN 2407-7658 | e-ISSN 2460-0040
Published By Department of Computer Science Universitas Negeri Semarang
Website: https://journal.unnes.ac.id/nju/index.php/sji
Email: [email protected]

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.