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http://hdl.handle.net/10603/13664
Title: | Tamil text image processing restoration and character recognition |
Researcher: | Selvakumar Raja S |
Guide(s): | Mala John |
Keywords: | Tamil, Image processing, restoration, character recognition, Expectation Maximization (EM), Discrete Wavelet Transform, Back Propagation Neural Network, Support Vector Machine |
Upload Date: | 5-Dec-2013 |
University: | Anna University |
Completed Date: | 2010 |
Abstract: | Tamil, one of the oldest languages in the world, is a South Indian language spoken widely in Tamil Nadu, one of the states of India. The significance of the thesis stems from the fact that the Tamil language is ancient and widespread, owning rich literature content. Realizing the research potential in Tamil Text image problem, this thesis is focused towards Tamil Text Image Restoration and Tamil Character Recognition. Processing of the Tamil Text image, like any other text image primarily involves two components: Restoration and Character recognition. This thesis addresses the problem of Tamil text image restoration and Tamil character recognition, which form the integral parts of Tamil text image processing. The issues related to Tamil character recognition could be either related to feature extraction or to classification. As both feature extraction and classification have equally important roles to play, this thesis addresses both of these problems. The initial part of the thesis is focused towards restoration of noisy Tamil Text Images. A spatially adaptive restoration algorithm based on Expectation Maximization (EM) operating in the wavelet transform domain is proposed. The second part is dedicated to Tamil character recognition in terms of feature extraction and classification. Two novel feature extraction methods viz. Slope method and Discrete Wavelet Transform (DWT) domain based method are proposed. The slope method makes use of identifying unique curves in the Tamil character set which can be effectively used for classification purpose. The feature vectors extracted from the proposed methods are fed as inputs to different classifiers viz. Back Propagation Neural Network (BPNN), Support Vector Machine (SVM), Decision Tree classifiers and their performance is experimentally validated. The feature extraction algorithms and the classifier algorithm presented herein prove to be promising candidates for Tamil character recognition. newline newline newline |
Pagination: | xix, 110 |
URI: | http://hdl.handle.net/10603/13664 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 25.34 kB | Adobe PDF | View/Open |
02_certificates.pdf | 128.51 kB | Adobe PDF | View/Open | |
03_abstract.pdf | 13.64 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 15.93 kB | Adobe PDF | View/Open | |
05_contents.pdf | 122.39 kB | Adobe PDF | View/Open | |
06_chapter 1.pdf | 146.63 kB | Adobe PDF | View/Open | |
07_chapter 2.pdf | 1.62 MB | Adobe PDF | View/Open | |
08_chapter 3.pdf | 110.3 kB | Adobe PDF | View/Open | |
09_chapter 4.pdf | 991.85 kB | Adobe PDF | View/Open | |
10_chapter 5.pdf | 107 kB | Adobe PDF | View/Open | |
11_references.pdf | 393.6 kB | Adobe PDF | View/Open | |
12_publications.pdf | 37.78 kB | Adobe PDF | View/Open | |
13_vitae.pdf | 13.13 kB | Adobe PDF | View/Open |
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