Performance Comparison of Denoising Methods for Historical Documents

Muchallil, Sayed; Arnia, Fitri; Munadi, Khairul; Fardian, Fardian

doi:10.11113/jt.v77.6676

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…dimana 𝑇 𝑤 adalah nilai ambang Wolf, 𝑀 adalah nilai minimum yang terdapat dalam suatu window dan nilai 𝑘 adalah 0,5. Beberapa peneliti telah melakukan kajian binerisasi untuk dokumen Jawi kuno, seperti Bataineh (Bataineh, Abdullah and Omar, 2015), Razak (Rzak, 2016), Muchallil (Muchallil et al, 2015), iNICK (Saddami et al, 2017), dan Local Otsu (Saddami et al, 2019). Hasil kajian menunjukkan bahwa tidak ada metode yang mempunyai performansi terbaik untuk dokumen Jawi kuno.…”

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

Saddami

Arnia

Away

et al. 2020

JTIIK

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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. AbstractAncient 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.

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

Saddami

Arnia

Away

et al. 2020

JTIIK

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“…Research in the digital image and computer vision field has yielded optical character recognition (OCR) for Chinese [5], Arabic [6], [7], Indian [8], and Latin characters [9], but no OCR system has yet been presented for Jawi characters. An OCR application framework requires four steps, namely: (1) preprocessing [10], [11], [12]; (2) segmentation; (3) feature extraction [13], [14]; and (4) pattern classiffiication [15]. At present, few algorithms for Jawi character recognition exist and these recognition algorithms have only been tested on a limited number of Jawi characters.…”

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confidence: 99%

Moment invariant-based features for Jawi character recognition

Arnia¹,

Saddami²,

Munadi³

2019

IJECE

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Ancient manuscripts written in Malay-Arabic characters, which are known as "Jawi" characters, are mostly found in Malay world. Nowadays, many of the manuscripts have been digitalized. Unlike Roman letters, there is no optical character recognition (OCR) software for Jawi characters. This article proposes a new algorithm for Jawi character recognition based on Hu’s moment as an invariant feature that we call the tree root (TR) algorithm. The TR algorithm allows every Jawi character to have a unique combination of moment. Seven values of the Hu’s moment are calculated from all Jawi characters, which consist of 36 isolated, 27 initial, 27 middle, and 35 end characters; this makes a total of 125 characters. The TR algorithm was then applied to recognize these characters. To assess the TR algorithm, five characters that had been rotated to 90o and 180o and scaled with factors of 0.5 and 2 were used. Overall, the recognition rate of the TR algorithm was 90.4%; 113 out of 125 characters have a unique combination of moment values, while testing on rotated and scaled characters achieved 82.14% recognition rate. The proposed method showed a superior performance compared with the Support Vector Machine and Euclidian Distance as classifier.

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“…Several researchers tested the method for Jawi ancient document [13][14][15][16]. The result of this testing informed the existing method did not perform well for Jawi ancient document.…”

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confidence: 99%

Improvement of binarization performance using local otsu thresholding

Saddami

Munadi

Away

et al. 2019

IJECE

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Ancient document usually contains multiple noises such as uneven-background, show-through, water-spilling, spots, and blur text. The noise will affect the binarization process. Binarization is an extremely important process in image processing, especially for character recognition. This paper presents an improvement to Nina binarization technique. Improvements were achieved by reducing processing steps and replacing median filtering by Wiener filtering. First, the document background was approximated by using Wiener filter, and then image subtraction was applied. Furthermore, the manuscript contrast was adjusted by mapping intensity of image value using intensity transformation method. Next, the local Otsu thresholding was applied. For removing spotting noise, we applied labeled connected component. The proposed method had been testing on H-DIBCO 2014 and degraded Jawi handwritten ancient documents. It performed better regarding recall and precision values, as compared to Otsu, Niblack, Sauvola, Lu, Su, and Nina, especially in the documents with show-through, water-spilling and combination noises.

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Performance Comparison of Denoising Methods for Historical Documents

Cited by 6 publications

References 11 publications

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

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

Moment invariant-based features for Jawi character recognition

Improvement of binarization performance using local otsu thresholding

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