Iterative cross section sequence graph for handwritten character segmentation
Identifieur interne : 000274 ( PascalFrancis/Checkpoint ); précédent : 000273; suivant : 000275Iterative cross section sequence graph for handwritten character segmentation
Auteurs : Amer Dawoud [Canada]Source :
- IEEE transactions on image processing [ 1057-7149 ] ; 2007.
Descripteurs français
- Pascal (Inist)
- Méthode itérative, Caractère manuscrit, Segmentation, Algorithme, Graphe conceptuel, Détection seuil, Perte information, Image binaire, Congestion trafic, Gestion trafic, Squelette, Extraction caractéristique, Evaluation performance, Reconnaissance optique caractère, Télétrafic, Traitement signal, Reconnaissance forme.
English descriptors
- KwdEn :
- Algorithm, Binary image, Conceptual graph, Feature extraction, Information loss, Iterative method, Manuscript character, Optical character recognition, Pattern recognition, Performance evaluation, Segmentation, Signal processing, Skeleton, Teletraffic, Threshold detection, Traffic congestion, Traffic management.
Abstract
-The iterative cross section sequence graph (ICSSG) is an algorithm for handwritten character segmentation. It expands the cross section sequence graph concept by applying it iteratively at equally spaced thresholds. The iterative thresholding reduces the effect of information loss associated with image binarization. ICSSG preserves the characters' skeletal structure by preventing the interference of pixels that causes flooding of adjacent characters' segments. Improving the structural quality of the characters' skeleton facilitates better feature extraction and classification, which improves the overall performance of optical character recognition (OCR). Experimental results showed significant improvements in OCR recognition rates compared to other well-established segmentation algorithms.
Affiliations:
Links toward previous steps (curation, corpus...)
Links to Exploration step
Pascal:07-0361762Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Iterative cross section sequence graph for handwritten character segmentation</title>
<author><name sortKey="Dawoud, Amer" sort="Dawoud, Amer" uniqKey="Dawoud A" first="Amer" last="Dawoud">Amer Dawoud</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Rotoflex International, Inc</s1>
<s2>Mississauga, ON L5T 2R5</s2>
<s3>CAN</s3>
<sZ>1 aut.</sZ>
</inist:fA14>
<country>Canada</country>
<wicri:noRegion>Mississauga, ON L5T 2R5</wicri:noRegion>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">07-0361762</idno>
<date when="2007">2007</date>
<idno type="stanalyst">PASCAL 07-0361762 INIST</idno>
<idno type="RBID">Pascal:07-0361762</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">000341</idno>
<idno type="wicri:Area/PascalFrancis/Curation">000445</idno>
<idno type="wicri:Area/PascalFrancis/Checkpoint">000274</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Iterative cross section sequence graph for handwritten character segmentation</title>
<author><name sortKey="Dawoud, Amer" sort="Dawoud, Amer" uniqKey="Dawoud A" first="Amer" last="Dawoud">Amer Dawoud</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Rotoflex International, Inc</s1>
<s2>Mississauga, ON L5T 2R5</s2>
<s3>CAN</s3>
<sZ>1 aut.</sZ>
</inist:fA14>
<country>Canada</country>
<wicri:noRegion>Mississauga, ON L5T 2R5</wicri:noRegion>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">IEEE transactions on image processing</title>
<title level="j" type="abbreviated">IEEE trans. image process.</title>
<idno type="ISSN">1057-7149</idno>
<imprint><date when="2007">2007</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">IEEE transactions on image processing</title>
<title level="j" type="abbreviated">IEEE trans. image process.</title>
<idno type="ISSN">1057-7149</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithm</term>
<term>Binary image</term>
<term>Conceptual graph</term>
<term>Feature extraction</term>
<term>Information loss</term>
<term>Iterative method</term>
<term>Manuscript character</term>
<term>Optical character recognition</term>
<term>Pattern recognition</term>
<term>Performance evaluation</term>
<term>Segmentation</term>
<term>Signal processing</term>
<term>Skeleton</term>
<term>Teletraffic</term>
<term>Threshold detection</term>
<term>Traffic congestion</term>
<term>Traffic management</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Méthode itérative</term>
<term>Caractère manuscrit</term>
<term>Segmentation</term>
<term>Algorithme</term>
<term>Graphe conceptuel</term>
<term>Détection seuil</term>
<term>Perte information</term>
<term>Image binaire</term>
<term>Congestion trafic</term>
<term>Gestion trafic</term>
<term>Squelette</term>
<term>Extraction caractéristique</term>
<term>Evaluation performance</term>
<term>Reconnaissance optique caractère</term>
<term>Télétrafic</term>
<term>Traitement signal</term>
<term>Reconnaissance forme</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">-The iterative cross section sequence graph (ICSSG) is an algorithm for handwritten character segmentation. It expands the cross section sequence graph concept by applying it iteratively at equally spaced thresholds. The iterative thresholding reduces the effect of information loss associated with image binarization. ICSSG preserves the characters' skeletal structure by preventing the interference of pixels that causes flooding of adjacent characters' segments. Improving the structural quality of the characters' skeleton facilitates better feature extraction and classification, which improves the overall performance of optical character recognition (OCR). Experimental results showed significant improvements in OCR recognition rates compared to other well-established segmentation algorithms.</div>
</front>
</TEI>
<inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>1057-7149</s0>
</fA01>
<fA03 i2="1"><s0>IEEE trans. image process.</s0>
</fA03>
<fA05><s2>16</s2>
</fA05>
<fA06><s2>8</s2>
</fA06>
<fA08 i1="01" i2="1" l="ENG"><s1>Iterative cross section sequence graph for handwritten character segmentation</s1>
</fA08>
<fA11 i1="01" i2="1"><s1>DAWOUD (Amer)</s1>
</fA11>
<fA14 i1="01"><s1>Rotoflex International, Inc</s1>
<s2>Mississauga, ON L5T 2R5</s2>
<s3>CAN</s3>
<sZ>1 aut.</sZ>
</fA14>
<fA20><s1>2150-2154</s1>
</fA20>
<fA21><s1>2007</s1>
</fA21>
<fA23 i1="01"><s0>ENG</s0>
</fA23>
<fA43 i1="01"><s1>INIST</s1>
<s2>22520</s2>
<s5>354000161639420210</s5>
</fA43>
<fA44><s0>0000</s0>
<s1>© 2007 INIST-CNRS. All rights reserved.</s1>
</fA44>
<fA45><s0>13 ref.</s0>
</fA45>
<fA47 i1="01" i2="1"><s0>07-0361762</s0>
</fA47>
<fA60><s1>P</s1>
<s3>CR</s3>
</fA60>
<fA61><s0>A</s0>
</fA61>
<fA64 i1="01" i2="1"><s0>IEEE transactions on image processing</s0>
</fA64>
<fA66 i1="01"><s0>USA</s0>
</fA66>
<fC01 i1="01" l="ENG"><s0>-The iterative cross section sequence graph (ICSSG) is an algorithm for handwritten character segmentation. It expands the cross section sequence graph concept by applying it iteratively at equally spaced thresholds. The iterative thresholding reduces the effect of information loss associated with image binarization. ICSSG preserves the characters' skeletal structure by preventing the interference of pixels that causes flooding of adjacent characters' segments. Improving the structural quality of the characters' skeleton facilitates better feature extraction and classification, which improves the overall performance of optical character recognition (OCR). Experimental results showed significant improvements in OCR recognition rates compared to other well-established segmentation algorithms.</s0>
</fC01>
<fC02 i1="01" i2="X"><s0>001D04A05C</s0>
</fC02>
<fC02 i1="02" i2="X"><s0>001D04A05A</s0>
</fC02>
<fC02 i1="03" i2="X"><s0>001D04A05D</s0>
</fC02>
<fC03 i1="01" i2="X" l="FRE"><s0>Méthode itérative</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="ENG"><s0>Iterative method</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="SPA"><s0>Método iterativo</s0>
<s5>01</s5>
</fC03>
<fC03 i1="02" i2="X" l="FRE"><s0>Caractère manuscrit</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="ENG"><s0>Manuscript character</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="SPA"><s0>Carácter manuscrito</s0>
<s5>02</s5>
</fC03>
<fC03 i1="03" i2="X" l="FRE"><s0>Segmentation</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="ENG"><s0>Segmentation</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="SPA"><s0>Segmentación</s0>
<s5>03</s5>
</fC03>
<fC03 i1="04" i2="X" l="FRE"><s0>Algorithme</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="X" l="ENG"><s0>Algorithm</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="X" l="SPA"><s0>Algoritmo</s0>
<s5>04</s5>
</fC03>
<fC03 i1="05" i2="X" l="FRE"><s0>Graphe conceptuel</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="X" l="ENG"><s0>Conceptual graph</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="X" l="SPA"><s0>Grafo conceptual</s0>
<s5>05</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Détection seuil</s0>
<s5>06</s5>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Threshold detection</s0>
<s5>06</s5>
</fC03>
<fC03 i1="06" i2="X" l="SPA"><s0>Detección umbral</s0>
<s5>06</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE"><s0>Perte information</s0>
<s5>07</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG"><s0>Information loss</s0>
<s5>07</s5>
</fC03>
<fC03 i1="07" i2="X" l="SPA"><s0>Pérdida información</s0>
<s5>07</s5>
</fC03>
<fC03 i1="08" i2="X" l="FRE"><s0>Image binaire</s0>
<s5>08</s5>
</fC03>
<fC03 i1="08" i2="X" l="ENG"><s0>Binary image</s0>
<s5>08</s5>
</fC03>
<fC03 i1="08" i2="X" l="SPA"><s0>Imagen binaria</s0>
<s5>08</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Congestion trafic</s0>
<s5>09</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Traffic congestion</s0>
<s5>09</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Congestión tráfico</s0>
<s5>09</s5>
</fC03>
<fC03 i1="10" i2="X" l="FRE"><s0>Gestion trafic</s0>
<s5>10</s5>
</fC03>
<fC03 i1="10" i2="X" l="ENG"><s0>Traffic management</s0>
<s5>10</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA"><s0>Gestión tráfico</s0>
<s5>10</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE"><s0>Squelette</s0>
<s5>11</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG"><s0>Skeleton</s0>
<s5>11</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Esqueleto</s0>
<s5>11</s5>
</fC03>
<fC03 i1="12" i2="3" l="FRE"><s0>Extraction caractéristique</s0>
<s5>12</s5>
</fC03>
<fC03 i1="12" i2="3" l="ENG"><s0>Feature extraction</s0>
<s5>12</s5>
</fC03>
<fC03 i1="13" i2="X" l="FRE"><s0>Evaluation performance</s0>
<s5>13</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Performance evaluation</s0>
<s5>13</s5>
</fC03>
<fC03 i1="13" i2="X" l="SPA"><s0>Evaluación prestación</s0>
<s5>13</s5>
</fC03>
<fC03 i1="14" i2="X" l="FRE"><s0>Reconnaissance optique caractère</s0>
<s5>14</s5>
</fC03>
<fC03 i1="14" i2="X" l="ENG"><s0>Optical character recognition</s0>
<s5>14</s5>
</fC03>
<fC03 i1="14" i2="X" l="SPA"><s0>Reconocimento óptico de caracteres</s0>
<s5>14</s5>
</fC03>
<fC03 i1="15" i2="X" l="FRE"><s0>Télétrafic</s0>
<s5>31</s5>
</fC03>
<fC03 i1="15" i2="X" l="ENG"><s0>Teletraffic</s0>
<s5>31</s5>
</fC03>
<fC03 i1="15" i2="X" l="SPA"><s0>Teletráfico</s0>
<s5>31</s5>
</fC03>
<fC03 i1="16" i2="X" l="FRE"><s0>Traitement signal</s0>
<s5>32</s5>
</fC03>
<fC03 i1="16" i2="X" l="ENG"><s0>Signal processing</s0>
<s5>32</s5>
</fC03>
<fC03 i1="16" i2="X" l="SPA"><s0>Procesamiento señal</s0>
<s5>32</s5>
</fC03>
<fC03 i1="17" i2="X" l="FRE"><s0>Reconnaissance forme</s0>
<s5>33</s5>
</fC03>
<fC03 i1="17" i2="X" l="ENG"><s0>Pattern recognition</s0>
<s5>33</s5>
</fC03>
<fC03 i1="17" i2="X" l="SPA"><s0>Reconocimiento patrón</s0>
<s5>33</s5>
</fC03>
<fN21><s1>232</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
</standard>
</inist>
<affiliations><list><country><li>Canada</li>
</country>
</list>
<tree><country name="Canada"><noRegion><name sortKey="Dawoud, Amer" sort="Dawoud, Amer" uniqKey="Dawoud A" first="Amer" last="Dawoud">Amer Dawoud</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/OcrV1/Data/PascalFrancis/Checkpoint
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000274 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PascalFrancis/Checkpoint/biblio.hfd -nk 000274 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Ticri/CIDE |area= OcrV1 |flux= PascalFrancis |étape= Checkpoint |type= RBID |clé= Pascal:07-0361762 |texte= Iterative cross section sequence graph for handwritten character segmentation }}
![]() | This area was generated with Dilib version V0.6.32. | ![]() |