Kombinasi Metode Nilai Ambang Lokal dan Global untuk Restorasi Dokumen Jawi Kuno

Penulis

DOI:

https://doi.org/10.25126/jtiik.2020701741

Abstrak

Dokumen Jawi kuno merupakan warisan budaya yang berisi informasi penting tentang peradaban masa lalu yang dapat dijadikan pedoman untuk masa sekarang ini. Dokumen Jawi kuno telah mengalami penurunan kualitas yang disebabkan oleh beberapa faktor seperti kualitas kertas atau karena proses penyimpanan. Penurunan kualitas ini menyebabkan informasi yang terdapat pada dokumen tersebut menghilang dan sulit untuk diakses. Artikel ini mengusulkan metode binerisasi untuk membangkitkan kembali informasi yang terdapat pada dokumen Jawi kuno. Metode usulan merupakan kombinasi antara metode binerisasi berbasis nilai ambang lokal dan global. Metode usulan diuji terhadap dokumen Jawi kuno dan dokumen uji standar yang dikenal dengan nama Handwritten Document Image Binarization Contest (HDIBCO) 2016. Citra hasil binerisasi dievaluasi menggunakan metode: F-measure, pseudo F-measure, peak signal-to-noise ratio, distance reciprocal distortion, dan misclasification penalty metric. Secara rata-rata, nilai evaluasi F-measure dari metode usulan mencapai 88,18 dan 89,04 masing-masing untuk dataset Jawi dan HDIBCO-2016. Hasil ini lebih baik dari metode pembanding yang menunjukkan bahwa metode usulan berhasil meningkatkan kinerja metode binerisasi untuk dataset Jawi dan HDIBCO-2016.

 

Abstract

Ancient Jawi document is a cultural heritage, which contains knowledge of past civilization for developing a better future. Ancient Jawi document suffers from severe degradation due to some factors such as paper quality or poor retention process. The degradation reduces information on the document and thus the information is difficult to access. This paper proposed a binarization method for restoring the information from degraded ancient Jawi document. The proposed method combined a local and global thresholding method for extracting the text from the background. The experiment was conducted on ancient Jawi document and Handwritten Document Image Binarization Contest (HDIBCO) 2016 datasets. The result was evaluated using F-measure, pseudo F-measure, peak signal-to-noise ratio, distance reciprocal distortion, dan misclassification penalty metric. The average result showed that the proposed method achieved 88.18 and 89.04 of F-measure, for Jawi and HDIBCO-2016, respectively. The proposed method resulted in better performance compared with several benchmarking methods. It can be concluded that the proposed method succeeded to enhance binarization performance.


Downloads

Download data is not yet available.

Referensi

ARNIA, F. AND MUNADI, K., 2017. Binarization of Ancient Document Images based on Multipeak Histogram Assumption. Telkomnika, 15(3).

ARNIA, F., MUNADI, K., FARDIAN AND MUCHALLIL, S., 2014. Improvement of binarization performance by applying DCT as pre-processing procedure. In: ISCCSP 2014 - 2014 6th International Symposium on Communications, Control and Signal Processing, Proceedings. pp.128–132.

BATAINEH, B., ABDULLAH, S.N.H.S. AND OMAR, K., 2015. Adaptive binarization method for degraded document images based on surface contrast variation. Pattern Analysis and Applications, pp.1–14.

FARDIAN, ARNIA, F., MUCHALLIL, S. AND MUNADI, K., 2015. Identification of most suitable binarisation methods for acehnese ancient manuscripts restoration software user guide. Jurnal Teknologi, 77(22), p.95–102.

GATOS, B., NTIROGIANNIS, K. AND PRATIKAKIS, I., 2011. DIBCO 2009: Document image binarization contest. International Journal on Document Analysis and Recognition, 14(1), pp.35–44.

KHURSHID, K., SIDDIQI, I., FAURE, C. AND VINCENT, N., 2009. Comparison of Niblack inspired Binarization methods for ancient documents. In: IS&T/SPIE Electronic Imaging. p.72470U--72470U.

LECH, P., 2015. Binarization of document images using the modified local-global Otsu and Kapur algorithms. Przegląd Elektrotechniczny, [online] 1(2), pp.73–76. Available at: <http://sigma-not.pl/publikacja-89353-2015-2.html>.

MUCHALLIL, S., ARNIA, F., MUNADI, K. AND FARDIAN, 2015. Performance comparison of denoising methods for historical documents. Jurnal Teknologi, 77(22), pp.137–143.

OTSU, N., 1979. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, [online] 9(1), pp.62–66. Available at: <http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4310076>.

PRATIKAKIS, I., ZAGORIS, K., BARLAS, G. AND GATOS, B., 2016. ICFHR2016 Handwritten Document Image Binarization Contest (H-DIBCO 2016). In: Frontiers in Handwriting Recognition (ICFHR), 2016 15th International Conference on. pp.619–623.

SADDAMI, K., MUNADI, K., AWAY, Y. AND ARNIA, F., 2019. Improvement of Binarization Performance using Local Otsu Thresholding. International Journal of Electrical and Computer Engineering, 9(1), pp.264–272.

SADDAMI, K., MUNADI, K., MUCHALLIL, S. AND ARNIA, F., 2017. Improved Thresholding Method for Enhancing Jawi Binarization Performance. In: Document Analysis and Recognition, 2017. ICDAR’17. 14th International Conference on. pp.1108–1113.

SAFRIZAL, ARNIA, F. AND MUHARAR, R., 2016. Pengenalan Aksara Jawi Tulisan Tangan Menggunakan Freemen Chain Code ( Fcc ), Support Vector Machine ( Svm ) Dan Aturan Pengambilan Keputusan. Jurnal Nasional Teknik Elektro, 5(1), pp.45–55.

SARI, T., KEFALI, A. AND BAHI, H., 2014. Text extraction from historical document images by the combination of several thresholding techniques. Advances in Multimedia, 2014.

SAUVOLA, J. AND PIETIKÄINEN, M., 2000. Adaptive document image binarization. Pattern recognition, 33(2), pp.225–236.

SAXENA, L.P., 2017. Niblack’s binarization method and its modifications to real-time applications: a review. Artificial Intelligence Review, pp.1–33.

SEZGIN, M. AND SANKUR, B., 2004. Survey over image thresholding techniques and quantitative performance evaluation. Journal of Electronic Imaging, 13(1), pp.146–165.

WEN, J., LI, S. AND SUN, J., 2013. A new binarization method for non-uniform illuminated document images. Pattern Recognition, [online] 46(6), pp.1670–1690. Available at: <http://dx.doi.org/10.1016/j.patcog.2012.11.027>.

WOLF, C. AND JOLION, J.-M., 2004. Extraction and recognition of artificial text in multimedia documents. Pattern Analysis & Applications, 6(4), pp.309–326.

YAHAYA, D.M.H., 2016. The Jawi Manuscript: Its History, Role, and Function in the Malay Archipelago. Journal of Islamic Studies and Culture, [online] 4(1), pp.52–61. Available at: <http://jiscnet.com/vol-4-no-1-june-2016-abstract-7-jisc>.

Diterbitkan

04-02-2020

Terbitan

Bagian

Ilmu Komputer

Cara Mengutip

Kombinasi Metode Nilai Ambang Lokal dan Global untuk Restorasi Dokumen Jawi Kuno. (2020). Jurnal Teknologi Informasi Dan Ilmu Komputer, 7(1), 163-170. https://doi.org/10.25126/jtiik.2020701741