Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/226723
Full metadata record
DC FieldValueLanguage
dc.coverage.spatialText recognition
dc.date.accessioned2019-01-24T11:29:51Z-
dc.date.available2019-01-24T11:29:51Z-
dc.identifier.urihttp://hdl.handle.net/10603/226723-
dc.description.abstractText recognition is a process by which computer recognizes the written or printed characters newlinesuch as words, letters, numbers and to change them into a form that the computer can newlineunderstand and make use of it further. There is a great influence of computers on the lives of newlinehuman beings since the computer usage has an immense importance in the day to day activities. newlineText recognition can be treated as the fastest and very natural way of communicating computer newlinesystem by a human being. The bank cheque processing, automatic data entry, retrieval of text newlinefrom old documents are some of the important areas of applications. Researchers have already newlineproposed many recognition systems and approaches for printed and handwritten character newlinerecognition in English, Chinese etc. languages. In the Indian context, Devanagari script has newlinebeen given attention by the researchers for three decades. But there are many languages which newlineare yet to be attended in Devanagari script. In this thesis attention has been given to the very newlineancient Indian languages such as Pali - a language which is also referred as Aadi-Prakrut or newlineMagadhi and another language which has been focused in this thesis is the Marathi language. newlineA novel approach is devised for identifying isolated handwritten Pali characters. In this newlinework, the structural and the features of Gabor filter are considered. Using structural features, newlinea feature vector comprising of the density of total pixels, height, width and area is calculated. newlineAdditionally, 16 features of Gabor filter are considered and the decision tree is employed for newlinethe purpose of classification. It is observed that the proposed system achieves 96.25% newlinerecognition accuracy, tested over 26240 handwritten Pali characters. Another approach to newlinerecognize handwritten Devanagari characters is also performed using a combination of newlinequadratic and SVM classifiers. Here, features like directional features that are strength, angle newlineand histogram of gradient are employed. Gaussian filters are used to downsample the features newlineto obtain a
dc.format.extent109p
dc.languageEnglish
dc.relation153b
dc.rightsuniversity
dc.titleDocument text Recognition
dc.title.alternativen.a.
dc.creator.researcherBhalerao Milind Vithalrao
dc.subject.keywordEngineering and Technology,Computer Science,Computer Science Information Systems
dc.description.noteBibliiography
dc.contributor.guideBonde S. V.
dc.publisher.placeNanded
dc.publisher.universitySwami Ramanand Teerth Marathwada University
dc.publisher.institutionFaculty of Engineering
dc.date.registered11/11/2011
dc.date.completed23/03/2018
dc.date.awarded03/08/2018
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File148.4 kBAdobe PDFView/Open
02_certificate.pdf76.51 kBAdobe PDFView/Open
03_abstract.pdf165.38 kBAdobe PDFView/Open
04_acknoledgement.pdf108.45 kBAdobe PDFView/Open
06_lis_of_tables.pdf105.34 kBAdobe PDFView/Open
07_list_of-figures.pdf144.09 kBAdobe PDFView/Open
08_chapter 1.pdf1.05 MBAdobe PDFView/Open
09_chapter 2.pdf196.44 kBAdobe PDFView/Open
10_chapter 3.pdf288.8 kBAdobe PDFView/Open
11_chapter 4.pdf351.63 kBAdobe PDFView/Open
12_chapter5.pdf1.77 MBAdobe PDFView/Open
13_chapter 6.pdf112.39 kBAdobe PDFView/Open
14_bibliography.pdf207.25 kBAdobe PDFView/Open


Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Altmetric Badge: