Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/535634
Title: | Converting Handwritten Medieval Devnagari Manuscript Character into Recent Devnagari Script Character |
Researcher: | Mehta, Nikita |
Guide(s): | Doshi, Jyotika |
Keywords: | Computer Science Computer Science Information Systems Devnagri Manuscript Engineering and Technology |
University: | GLS University |
Completed Date: | 2021 |
Abstract: | The proposed research is titled as Converting Handwritten Medieval Devnagari newlineManuscript Character into Recent Devnagari Script Character . The main aim of newlinethis research is to recognize handwritten medieval Devnagari script character and newlineconvert it into recent Devnagari script character. The writing style of Medieval newlineDevnagari script characters is different than the recent Devnagari script. Additionally, newlinesome character symbols used in medieval Devnagari script are different than recent newlineDevnagari script. That is why the manuscripts written in medieval Devnagari is not newlinereadable to everyone who can read the recent Devnagari script. Moreover, these newlinemanuscripts are aged from hundreds to a thousand years. Due to aging, they are in very newlinefragile condition. It is risky to hand over them directly to anybody. The major objective newlineof this research is to make this literature treasure available to a wider audience, and also newlineto conserve and preserve its content for longer period of time. With this intention, a newlinesystem named Medieval Devnagari Character Recognition and Conversion newline(MDCRC) is proposed, designed and implemented here. This system works in two newlinepasses. The first pass is recognition of medieval Devnagari script character and second newlinepass is to convert recognized character into recent Devnagari script character. First pass newlineincludes pre-processing, segmentation, feature extraction, testing and training newlineprocesses. Preprocessing includes grayscale conversion, image binarization and newlinemargins removal. After preprocessing, line segmentation and character segmentation newlineare applied on pre-processed manuscript images to extract individual characters. newlineSegmented characters are identified using pattern matching with characters stored in newlinedatabase. Second pass is character conversion. newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/535634 |
Appears in Departments: | Department of Computer Application and IT |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
80_recommendation.pdf | Attached File | 555.14 kB | Adobe PDF | View/Open |
nikita annexures.pdf | 10.64 MB | Adobe PDF | View/Open | |
nikita chapter1.pdf | 335.23 kB | Adobe PDF | View/Open | |
nikita chapter2.pdf | 1.46 MB | Adobe PDF | View/Open | |
nikita chapter6.pdf | 3.86 MB | Adobe PDF | View/Open | |
nikita chapter7.pdf | 401.3 kB | Adobe PDF | View/Open | |
nikita chapter8.pdf | 386.22 kB | Adobe PDF | View/Open | |
nikita chapter9.pdf | 189.52 kB | Adobe PDF | View/Open | |
nikita full thesis.pdf | 555.14 kB | Adobe PDF | View/Open | |
nikita_title.pdf | 14.35 kB | Adobe PDF | View/Open |
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