Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/424094
Title: | Online Handwritten Character and Word Recognition in Indic scripts |
Researcher: | Ghosh, Rajib |
Guide(s): | Kumar, Prabhat |
Keywords: | Computer Science Computer Science Artificial Intelligence Engineering and Technology |
University: | National Institute of Technology Patna |
Completed Date: | 2018 |
Abstract: | Online handwriting recognition problem has been well known in pattern recognition and machine learning community for long. But, it is still a challenging newlinetask to recognize accurately the online handwritten texts written in various Indic newlinescripts like Devanagari, Bengali, Telugu and Tamil. These are four most popular Indic scripts. The works available in the literature on these Indic scripts newlinevary from one script to other. Regarding character level recognition, researchers newlinehave worked on Devanagari and Tamil scripts with both simple and compound newlinecharacter recognition but works in Bengali script are confined only within simple characters. Real time requirements are for texts having both characters as newlinewell as numerals. None of these scripts have been analyzed with numerals in newlinecombination with characters. The present research work proposes two different newlineapproaches - one without combining the outcomes of Support Vector Machine newline(SVM) and Hidden Markov Model (HMM) classifiers and the other by combining the outcomes of these two classifiers, to recognize both online handwritten newlinesimple and compound characters as well as numerals in Devanagari, Bengali and newlineTamil scripts. The present research work trains the system initially by generating newlineseparate training datasets for numerals, simple characters and compound characters and then a single training dataset for all these symbols. The first approach newlineproposes novel zone-based feature extraction approaches, one of which is used newlinein the second approach as well. Regarding isolated word level recognition, little newlinenumber of research works are available in Devanagari, Bengali and Tamil scripts, newlinebut works in Telugu script are confined within only character level recognition. newlineThe present work also proposes two different approaches to develop an online newlinehandwritten script identification and isolated word recognition system in different Indic scripts. |
Pagination: | xx, 144p. |
URI: | http://hdl.handle.net/10603/424094 |
Appears in Departments: | Computer Science and Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 141.1 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 231.45 kB | Adobe PDF | View/Open | |
03_content.pdf | 97.53 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 72.32 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 318.15 kB | Adobe PDF | View/Open | |
06_chpater 2.pdf | 95.91 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 380.72 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.2 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 813.96 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 356.15 kB | Adobe PDF | View/Open | |
11_chapter 7.pdf | 1.6 MB | Adobe PDF | View/Open | |
12_chapter 8.pdf | 1.31 MB | Adobe PDF | View/Open | |
13_chapter 9.pdf | 71.51 kB | Adobe PDF | View/Open | |
14_annexures.pdf | 94.04 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 143.85 kB | Adobe PDF | View/Open |
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