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Segmentation of Bangla handwritten text

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dc.contributor.advisor Khan, Mumit
dc.contributor.author Sadik, Sabbir
dc.contributor.author Sarwar, Md. Numan
dc.date.accessioned 2012-09-12T10:00:32Z
dc.date.available 2012-09-12T10:00:32Z
dc.date.copyright 2012
dc.date.issued 2012-08-13
dc.identifier.other ID 09301027
dc.identifier.other ID 09201027
dc.identifier.uri http://hdl.handle.net/10361/1974
dc.description This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2012. en_US
dc.description Cataloged from PDF version of thesis report.
dc.description Includes bibliographical references (page 17).
dc.description.abstract Segmentation of handwritten text is the pre-process of recognition of handwritten text. Because of skewed lines, touching characters and different writing styles, segmentation of handwritten text is difficult than printed text. Correct segmentation is necessary to recognize the characters properly. That’s why a good segmentation is needed. Segmentation of Bangla handwritten text is a great challenge because of its complex characteristics. Till now there are very few works on Bangla handwritten text segmentation and still there are some problems that can’t be solved. After analyzing some methods and techniques that have already been done, here we propose a recursive algorithm for line, word and character segmentation. The algorithm works well if there is no overlapping situation between lines and characters as well. en_US
dc.description.statementofresponsibility Sabbir Sadik
dc.description.statementofresponsibility Md. Numan Sarwar
dc.format.extent 18 pages
dc.language.iso en
dc.publisher BRAC University en_US
dc.rights BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subject Computer science and engineering
dc.title Segmentation of Bangla handwritten text en_US
dc.type Thesis en_US
dc.contributor.department Department of Computer Science and Engineering, BRAC University
dc.description.degree B. Computer Science and Engineering


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