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Identification of most suitable binarisation methods for acehnese ancient manuscripts restoration software user guide
Fardian1, Fitri Arnia2, Sayed Muchallil3, Khairul Munadi4.
The Aceh Museum stores many digitized ancient manuscripts from hundreds of years ago. The condition of those manuscripts has degraded into several degradation types such as uneven contrast, show through effects, background spots, and text fading, which cause decreasing readability. A binarisation method is used to decrease the degradation effect on ancient manuscripts. Our research team is currently working on developing application software that consists of five binarisation methods, namely Otsu, Niblack, Sauvola, Lu, and Su for ancient manuscript restoration for the Aceh Museum staff to improve documents’ readability. In practice, a user still finds it difficult to choose the best method because there is no method that works best on every ancient manuscript for different types of degradation. This paper intends to determine a binarisation method that suits most manuscript conditions. The method used in this research includes the identification and classification of degradation types from 200 ancient Aceh digital manuscripts, followed by cropping the manuscripts to the size of 256 x 256 pixels. As many as five cropped areas from each degradation type are selected as research samples. These samples are binarisated using the methods. The last step is finding the most suitable binarisation method for each degradation type and classifying which methods are considered to have good readability, and that achieves at least 80% recall and precision values. From our experiments, we found that the Su binarisation methods demonstrate the best performance overall for every degradation type. Otsu, Lu, and Su are suited for uneven background; Sauvola, Lu, and Su are suited for showthrough effects; Otsu, Sauvola, and Su are suited for background spots; and Otsu and Su are suited for both text and background blurring and ‘fox’.
Affiliation:
- Universitas Syiah Kuala, Indonesia
- Universitas Syiah Kuala, Indonesia
- Universitas Syiah Kuala, Indonesia
- Universitas Syiah Kuala, Indonesia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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