2023
DOI: 10.1371/journal.pone.0282142
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Restoration and content analysis of ancient manuscripts via color space based segmentation

Abstract: Ancient manuscripts are a rich source of history and civilization. Unfortunately, these documents are often affected by different age and storage related degradation which impinge on their readability and information contents. In this paper, we propose a document restoration method that removes the unwanted interfering degradation patterns from color ancient manuscripts. We exploit different color spaces to highlight the spectral differences in various layers of information usually present in these documents. … Show more

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Cited by 3 publications
(2 citation statements)
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References 34 publications
(46 reference statements)
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“…He et al [11] proposed a novel DL-based document-enhancement-and-binarization model (DeepOtsu), utilizing iterative refinement and superposition to achieve visually pleasing results. Hanif et al [12] proposed a document-restoration method aimed at eliminating unwanted interfering degradation patterns from ancient manuscripts containing color.…”
Section: Related Work 21 Show-through-removal Methodsmentioning
confidence: 99%
“…He et al [11] proposed a novel DL-based document-enhancement-and-binarization model (DeepOtsu), utilizing iterative refinement and superposition to achieve visually pleasing results. Hanif et al [12] proposed a document-restoration method aimed at eliminating unwanted interfering degradation patterns from ancient manuscripts containing color.…”
Section: Related Work 21 Show-through-removal Methodsmentioning
confidence: 99%
“…Indonesian ancient manuscripts, known for their cultural and linguistic diversity, represent an invaluable intellectual treasure (Dinesh et al, 2023;Hanif et al, 2023). These texts provide a window to the past, offering profound insights into Indonesia's cultural evolution (Sunarno & Rachman, 2023), history (Dinasheva et al, 2022), religion (Shamakhay et al, 2019), and science (Schettino et al, 2023).…”
Section: Introductionmentioning
confidence: 99%