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Characters Segmentation of Cursive Handwritten Words based on Contour Analysis and Neural Network Validation

Journal of ICT Research and Applications (JICTRA) · Vol. 5 No. 1 (2013) · pp. 1–16

DOI
10.5614/itbj.ict.2011.5.1.1
ISSN
2338-5499, 2337-5787
Published
2013-09-13
Publisher
DRI - ITB
Language
eng

Abstract

This paper presents a robust algorithm to identify the letter boundaries in images of unconstrained handwritten word. The proposed algorithm is based on vertical contour analysis. Proposed algorithm is performed to generate presegmentation by analyzing the vertical contours from right to left. The unwanted segmentation points are reduced using neural network validation to improve accuracy of segmentation. The neural network is utilized to validate segmentation points. The experiments are performed on the IAM benchmark database. The results are showing that the proposed algorithm capable to accurately locating the letter boundaries for unconstrained handwritten words.

Collaboration network of the authors

7 authors · 15 co-authorship links · 4 across different organisations

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  • University of Technology Malaysia
  • King Saud University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Mohammed Sayim KhalilKing Saud University4
Muhammad Khurram KhanKing Saud University4

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jictra/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Characters Segmentation of Cursive Handwritten Words based on Contour Analysis and Neural Network Validation</dc:title>
	<dc:creator>Kurniawan, Fajri</dc:creator>
	<dc:creator>Mohd. Rahim, Mohd. Shafry</dc:creator>
	<dc:creator>Sholihah, Ni'matus</dc:creator>
	<dc:creator>Rakhmadi, Akmal</dc:creator>
	<dc:creator>Mohamad, Dzulkifli</dc:creator>
	<dc:description xml:lang="en-US">This paper presents a robust algorithm to identify the letter boundaries in images of unconstrained handwritten word . The proposed algorithm is based on  vertical  contour  analysis.  Proposed  algorithm  is  performed  to  generate  presegmentation by analyzing the vertical contours from right to left. The unwanted segmentation  points  are  reduced  using  neural  network  validation  to  improve accuracy  of  segmentation.  The  neural  network  is  utilized  to  validate segmentation  points.  The  experiments  are  performed  on  the  IAM  benchmark database.  The  results  are  showing  that  the  proposed  algorithm  capable  to accurately locating the letter boundaries for unconstrained handwritten words.</dc:description>
	<dc:publisher xml:lang="en-US">DRI - ITB</dc:publisher>
	<dc:date>2013-09-13</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/jictra/article/view/204</dc:identifier>
	<dc:identifier>10.5614/itbj.ict.2011.5.1.1</dc:identifier>
	<dc:source xml:lang="en-US">Journal of ICT Research and Applications; Vol. 5 No. 1 (2011); 1-16</dc:source>
	<dc:source>2338-5499</dc:source>
	<dc:source>2337-5787</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jictra/article/view/204/198</dc:relation>
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