Cursive word analysis
Cursive script recognition is important in the automation of document processing. Due to the large variation of letter shapes and handwriting styles in unconstrained cursive handwriting, the domain is much more difficult than single character recognition. The uhimate goal of cursive word research is...
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Format: | Thesis |
Language: | English |
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2009
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Online Access: | http://hdl.handle.net/10356/20511 |
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author | Wang, Jiren. |
author2 | Leung, Maylor Karhang |
author_facet | Leung, Maylor Karhang Wang, Jiren. |
author_sort | Wang, Jiren. |
collection | NTU |
description | Cursive script recognition is important in the automation of document processing. Due to the large variation of letter shapes and handwriting styles in unconstrained cursive handwriting, the domain is much more difficult than single character recognition. The uhimate goal of cursive word research is to develop a machine which can read any unconstrained handwritten word with the same recognition capability as humans. If the features people use to recognize cursive words are properly described and used in a cursive word recognition system, it is expected that the computer can imitate what humans can do. |
first_indexed | 2024-10-01T04:23:26Z |
format | Thesis |
id | ntu-10356/20511 |
institution | Nanyang Technological University |
language | English |
last_indexed | 2024-10-01T04:23:26Z |
publishDate | 2009 |
record_format | dspace |
spelling | ntu-10356/205112020-09-27T20:15:34Z Cursive word analysis Wang, Jiren. Leung, Maylor Karhang School of Applied Science DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition Cursive script recognition is important in the automation of document processing. Due to the large variation of letter shapes and handwriting styles in unconstrained cursive handwriting, the domain is much more difficult than single character recognition. The uhimate goal of cursive word research is to develop a machine which can read any unconstrained handwritten word with the same recognition capability as humans. If the features people use to recognize cursive words are properly described and used in a cursive word recognition system, it is expected that the computer can imitate what humans can do. Master of Applied Science 2009-12-15T03:09:31Z 2009-12-15T03:09:31Z 1995 1995 Thesis http://hdl.handle.net/10356/20511 en NANYANG TECHNOLOGICAL UNIVERSITY 105 p. application/pdf |
spellingShingle | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition Wang, Jiren. Cursive word analysis |
title | Cursive word analysis |
title_full | Cursive word analysis |
title_fullStr | Cursive word analysis |
title_full_unstemmed | Cursive word analysis |
title_short | Cursive word analysis |
title_sort | cursive word analysis |
topic | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition |
url | http://hdl.handle.net/10356/20511 |
work_keys_str_mv | AT wangjiren cursivewordanalysis |