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Handwritten Character Recognition using Morphological Operators with Competitive Neural Trees

http://hdl.handle.net/20.500.12678/0000003550
c27b8955-48da-4464-b28e-6bae3dded72f
d9ed408f-ad30-4d8e-b17f-d70bb0499e0b
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9033.pdf 9033.pdf (763 Kb)
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Article
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Publication
Title
Title Handwritten Character Recognition using Morphological Operators with Competitive Neural Trees
Language en
Publication date 2011-05-05
Authors
Htike, Theingi
Thein, Yadana
Description
In this paper an attempt is made to developMyanmar handwritten character recognitionsystem. Character recognition is an importantarea in image processing and patternrecognition fields. The aim of characterrecognition is to translate human readablecharacters to machine readable characters. Thepaper describes the process of characterrecognition using morphological operators withthe competitive neural trees. The morphologicaloperators are used to extract the edge of eachcharacter image. Then, competitive neural trees(CNeT) are used for classification. It is one ofthe fast supervised neural networks with highperformance. The main advantage of the CNeT isits structured, self-organizing architecture thatallows for short learning and recall times. Highspeed recognition rates can be gained by usingCNeT.
Keywords
CNeT, Myanmar handwritten characters, morphological edge extraction
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/129
Journal articles
Ninth International Conference On Computer Applications (ICCA 2011)
Conference papers
Books/reports/chapters
Thesis/dissertations
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