Digital acquisition and character extraction from stone inscription images using modified fuzzy entropy-based adaptive thresholding

Devi, K. Durga; Maheswari, P. Uma

doi:10.1007/s00500-018-3610-2

Cited by 12 publications

(1 citation statement)

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“…The advent of image processing, data science, machine learning, and artificial intelligence presents a unique opportunity for the modern world to decipher and analyze ancient information. A substantial volume of Tamil historical documents, once stored in libraries, museums, and temples, is now being digitized and made accessible through digital platforms [4,5,6]. However, this digitization process is met with numerous challenges.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study: Enhancing Legibility of Ancient Indian Script Images from Diverse Stone Background Structures using 34 Different Pre-Processing Methods

Maheshwari

2023

Preprint

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In recent times, there has been a proactive effort by various institutions and organizations to preserve historic manuscripts as repositories of traditional knowledge and cultural heritage. Leveraging digital media and emerging technologies has proven to be an efficient way to safeguard these invaluable documents. Such technologies not only facilitate the extraction of knowledge from historic manuscripts but also hold promise for global applications. However, transforming inscribed stone artifacts into binary formats presents significant challenges due to angle distortion, subtle differences between foreground and background, background noise, variations in text size, and related issues. A pivotal aspect of effective image processing in preserving the rich information and wisdom encoded in stone inscriptions lies in employing appropriate pre-processing methods and techniques. This research paper places a special focus on elucidating various preprocessing techniques, encompassing resizing, grayscale conversion, enhancement of brightness and contrast, smoothening, noise removal, morphological operations, and thresholding. To comprehensively assess these techniques, we undertake a study involving stone inscription images extracted from the Tanjore Brihadeeswar Temple, dating back to the 11th century during the reign of Raja Raja Chola. This choice is informed by the manifold challenges associated with image correction, such as distortion and blurring. We undertake an evaluation encompassing a diverse array of stone background structures, including types like flawless-bright-moderately legible, dark-illegible, flawless-bright-illegible, flawless-dull, flawless-irregular-moderate, highly impaired-dark-legible, highly impaired-irregular-illegible, impaired-dark-moderate, impaired-dull-moderately legible, impaired-dusky dark-moderate, and very impaired-dusky dark-legible. Subsequently, the processed outputs are subjected to character recognition and information extraction, with a focus on comparing the outcomes of various pre-processing methods, including binarization and grayscale conversion. This study seeks to contribute insights into the most effective pre-processing strategies for enhancing the legibility and preservation of ancient Indian script images etched onto diverse stone background structures.

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Section: Introductionmentioning

confidence: 99%