Crucial combinations of parts for handwritten alphanumeric characters
Identifieur interne : 000D92 ( Istex/Corpus ); précédent : 000D91; suivant : 000D93Crucial combinations of parts for handwritten alphanumeric characters
Auteurs : Z. C. Li ; C. Y. SuenSource :
- Mathematical and Computer Modelling [ 0895-7177 ] ; 2000.
Abstract
A combining approach has been studied previously to integrate different parts of handwritten characters for their analysis and recognition. Perfect combinations, by which the characters can be identified with certainty, are important to pattern analysis and character recognition. However, a large number of possible combinations (e.g., 63 combinations for a character partitioned into six parts), also produce a lot of perfect combinations. Hence, it is necessary to determine which of them are most important. In this paper, we propose a methodology of finding the basic crucial combinations, and algorithms to compute them. Compared with perfect combinations, such basic crucial combinations are most significant to the character distinctiveness. Similarly, the largest confusion regions are also identified. Experimental studies have also been conducted using the 89 most frequently used patterns of 36 alphanumeric handprints, to obtain their basic crucial combinations and largest confusion combinations. The results indicate that the ratio of the number of basic crucial combinations to perfect combinations is only 12.6%, and the ratio of the number of the largest confusion regions to the total confusion combinations is 15.6%.
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DOI: 10.1016/S0895-7177(00)00065-0
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Suen</name><affiliation><mods:affiliation>Centre for Pattern Recognition and Machine Intelligence, Concordia University, Suite GM-606 1455 de Maisonneuve Blvd. West, Montreal, Quebec H.3G IMS, Canada</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:4B8AED8224EEF6AF136BDD6F26F634D1EA68C213</idno><date when="2000" year="2000">2000</date><idno type="doi">10.1016/S0895-7177(00)00065-0</idno><idno type="url">https://api.istex.fr/document/4B8AED8224EEF6AF136BDD6F26F634D1EA68C213/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000D92</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a">Crucial combinations of parts for handwritten alphanumeric characters</title><author><name sortKey="Li, Z C" sort="Li, Z C" uniqKey="Li Z" first="Z. C." last="Li">Z. C. Li</name><affiliation><mods:affiliation>Department of Applied Mathematics National Sun Yat-sen University, Kaohsiung, Taiwan 80424, R.O.C.</mods:affiliation></affiliation></author><author><name sortKey="Suen, C Y" sort="Suen, C Y" uniqKey="Suen C" first="C. Y." last="Suen">C. Y. Suen</name><affiliation><mods:affiliation>Centre for Pattern Recognition and Machine Intelligence, Concordia University, Suite GM-606 1455 de Maisonneuve Blvd. West, Montreal, Quebec H.3G IMS, Canada</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Mathematical and Computer Modelling</title><title level="j" type="abbrev">MCM</title><idno type="ISSN">0895-7177</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="2000">2000</date><biblScope unit="volume">31</biblScope><biblScope unit="issue">8–9</biblScope><biblScope unit="page" from="193">193</biblScope><biblScope unit="page" to="229">229</biblScope></imprint><idno type="ISSN">0895-7177</idno></series><idno type="istex">4B8AED8224EEF6AF136BDD6F26F634D1EA68C213</idno><idno type="DOI">10.1016/S0895-7177(00)00065-0</idno><idno type="PII">S0895-7177(00)00065-0</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0895-7177</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">A combining approach has been studied previously to integrate different parts of handwritten characters for their analysis and recognition. Perfect combinations, by which the characters can be identified with certainty, are important to pattern analysis and character recognition. However, a large number of possible combinations (e.g., 63 combinations for a character partitioned into six parts), also produce a lot of perfect combinations. Hence, it is necessary to determine which of them are most important. In this paper, we propose a methodology of finding the basic crucial combinations, and algorithms to compute them. Compared with perfect combinations, such basic crucial combinations are most significant to the character distinctiveness. Similarly, the largest confusion regions are also identified. Experimental studies have also been conducted using the 89 most frequently used patterns of 36 alphanumeric handprints, to obtain their basic crucial combinations and largest confusion combinations. The results indicate that the ratio of the number of basic crucial combinations to perfect combinations is only 12.6%, and the ratio of the number of the largest confusion regions to the total confusion combinations is 15.6%.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>Z.C. Li</name><affiliations><json:string>Department of Applied Mathematics National Sun Yat-sen University, Kaohsiung, Taiwan 80424, R.O.C.</json:string></affiliations></json:item><json:item><name>C.Y. Suen</name><affiliations><json:string>Centre for Pattern Recognition and Machine Intelligence, Concordia University, Suite GM-606 1455 de Maisonneuve Blvd. West, Montreal, Quebec H.3G IMS, Canada</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>Character recognition</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Handwritten characters</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Handwritten recognition</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Alphanumeric handprints</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Regional decomposition method</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Part combination</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Crucial part</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Perfect combinations</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Crucial combinations</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Confusion combinations</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Largest confusion combinations</value></json:item></subject><language><json:string>eng</json:string></language><abstract>A combining approach has been studied previously to integrate different parts of handwritten characters for their analysis and recognition. Perfect combinations, by which the characters can be identified with certainty, are important to pattern analysis and character recognition. However, a large number of possible combinations (e.g., 63 combinations for a character partitioned into six parts), also produce a lot of perfect combinations. Hence, it is necessary to determine which of them are most important. In this paper, we propose a methodology of finding the basic crucial combinations, and algorithms to compute them. Compared with perfect combinations, such basic crucial combinations are most significant to the character distinctiveness. Similarly, the largest confusion regions are also identified. Experimental studies have also been conducted using the 89 most frequently used patterns of 36 alphanumeric handprints, to obtain their basic crucial combinations and largest confusion combinations. The results indicate that the ratio of the number of basic crucial combinations to perfect combinations is only 12.6%, and the ratio of the number of the largest confusion regions to the total confusion combinations is 15.6%.</abstract><qualityIndicators><score>7.148</score><pdfVersion>1.2</pdfVersion><pdfPageSize>504 x 756 pts</pdfPageSize><refBibsNative>true</refBibsNative><keywordCount>11</keywordCount><abstractCharCount>1236</abstractCharCount><pdfWordCount>7243</pdfWordCount><pdfCharCount>48243</pdfCharCount><pdfPageCount>37</pdfPageCount><abstractWordCount>179</abstractWordCount></qualityIndicators><title>Crucial combinations of parts for handwritten alphanumeric characters</title><pii><json:string>S0895-7177(00)00065-0</json:string></pii><genre><json:string>research-article</json:string></genre><serie><genre></genre><language><json:string>unknown</json:string></language><title>Technical Report</title></serie><host><volume>31</volume><pii><json:string>S0895-7177(00)X0095-7</json:string></pii><pages><last>229</last><first>193</first></pages><issn><json:string>0895-7177</json:string></issn><issue>8–9</issue><genre><json:string>Journal</json:string></genre><language><json:string>unknown</json:string></language><title>Mathematical and Computer Modelling</title><publicationDate>2000</publicationDate></host><categories><wos><json:string>COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS</json:string><json:string>COMPUTER SCIENCE, SOFTWARE ENGINEERING</json:string><json:string>MATHEMATICS, APPLIED</json:string></wos></categories><publicationDate>2000</publicationDate><copyrightDate>2000</copyrightDate><doi><json:string>10.1016/S0895-7177(00)00065-0</json:string></doi><id>4B8AED8224EEF6AF136BDD6F26F634D1EA68C213</id><fulltext><json:item><original>true</original><mimetype>application/pdf</mimetype><extension>pdf</extension><uri>https://api.istex.fr/document/4B8AED8224EEF6AF136BDD6F26F634D1EA68C213/fulltext/pdf</uri></json:item><json:item><original>true</original><mimetype>text/plain</mimetype><extension>txt</extension><uri>https://api.istex.fr/document/4B8AED8224EEF6AF136BDD6F26F634D1EA68C213/fulltext/txt</uri></json:item><json:item><original>false</original><mimetype>application/zip</mimetype><extension>zip</extension><uri>https://api.istex.fr/document/4B8AED8224EEF6AF136BDD6F26F634D1EA68C213/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/4B8AED8224EEF6AF136BDD6F26F634D1EA68C213/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a">Crucial combinations of parts for handwritten alphanumeric characters</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>ELSEVIER</publisher><availability><p>ELSEVIER</p></availability><date>2000</date></publicationStmt><notesStmt><note>This work was supported in part by National Sciences Council of Republic of China, by the Natural Sciences and Engineering Research Council of Canada, and by the Fonds pour la Formation de Chercheurs et l'Aide à la Recherche of Québec, the Ministère de l'Enseignement Superieur et de la Science.</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a">Crucial combinations of parts for handwritten alphanumeric characters</title><author><persName><forename type="first">Z.C.</forename><surname>Li</surname></persName><note type="biography">We are grateful to J. Guo for assistance in computer programming and data analysis in this paper.</note><affiliation>We are grateful to J. Guo for assistance in computer programming and data analysis in this paper.</affiliation><affiliation>Department of Applied Mathematics National Sun Yat-sen University, Kaohsiung, Taiwan 80424, R.O.C.</affiliation></author><author><persName><forename type="first">C.Y.</forename><surname>Suen</surname></persName><note type="biography">We are grateful to J. Guo for assistance in computer programming and data analysis in this paper.</note><affiliation>We are grateful to J. Guo for assistance in computer programming and data analysis in this paper.</affiliation><affiliation>Centre for Pattern Recognition and Machine Intelligence, Concordia University, Suite GM-606 1455 de Maisonneuve Blvd. West, Montreal, Quebec H.3G IMS, Canada</affiliation></author></analytic><monogr><title level="j">Mathematical and Computer Modelling</title><title level="j" type="abbrev">MCM</title><idno type="pISSN">0895-7177</idno><idno type="PII">S0895-7177(00)X0095-7</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="2000"></date><biblScope unit="volume">31</biblScope><biblScope unit="issue">8–9</biblScope><biblScope unit="page" from="193">193</biblScope><biblScope unit="page" to="229">229</biblScope></imprint></monogr><idno type="istex">4B8AED8224EEF6AF136BDD6F26F634D1EA68C213</idno><idno type="DOI">10.1016/S0895-7177(00)00065-0</idno><idno type="PII">S0895-7177(00)00065-0</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2000</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>A combining approach has been studied previously to integrate different parts of handwritten characters for their analysis and recognition. Perfect combinations, by which the characters can be identified with certainty, are important to pattern analysis and character recognition. However, a large number of possible combinations (e.g., 63 combinations for a character partitioned into six parts), also produce a lot of perfect combinations. Hence, it is necessary to determine which of them are most important. In this paper, we propose a methodology of finding the basic crucial combinations, and algorithms to compute them. Compared with perfect combinations, such basic crucial combinations are most significant to the character distinctiveness. Similarly, the largest confusion regions are also identified. Experimental studies have also been conducted using the 89 most frequently used patterns of 36 alphanumeric handprints, to obtain their basic crucial combinations and largest confusion combinations. The results indicate that the ratio of the number of basic crucial combinations to perfect combinations is only 12.6%, and the ratio of the number of the largest confusion regions to the total confusion combinations is 15.6%.</p></abstract><textClass><keywords scheme="keyword"><list><head>Keywords</head><item><term>Character recognition</term></item><item><term>Handwritten characters</term></item><item><term>Handwritten recognition</term></item><item><term>Alphanumeric handprints</term></item><item><term>Regional decomposition method</term></item><item><term>Part combination</term></item><item><term>Crucial part</term></item><item><term>Perfect combinations</term></item><item><term>Crucial combinations</term></item><item><term>Confusion combinations</term></item><item><term>Largest confusion combinations</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2000">Published</change></revisionDesc></teiHeader></istex:fulltextTEI></fulltext><metadata><istex:metadataXml wicri:clean="Elsevier, elements deleted: tail"><istex:xmlDeclaration>version="1.0" encoding="utf-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//ES//DTD journal article DTD version 4.5.2//EN//XML" URI="art452.dtd" name="istex:docType"></istex:docType><istex:document><converted-article version="4.5.2" docsubtype="fla"><item-info><jid>MCM</jid><aid>00000650</aid><ce:pii>S0895-7177(00)00065-0</ce:pii><ce:doi>10.1016/S0895-7177(00)00065-0</ce:doi><ce:copyright type="unknown" year="2000"></ce:copyright></item-info><head><ce:article-footnote><ce:label>☆</ce:label><ce:note-para>This work was supported in part by National Sciences Council of Republic of China, by the Natural Sciences and Engineering Research Council of Canada, and by the Fonds pour la Formation de Chercheurs et l'Aide à la Recherche of Québec, the Ministère de l'Enseignement Superieur et de la Science.</ce:note-para></ce:article-footnote><ce:title>Crucial combinations of parts for handwritten alphanumeric characters</ce:title><ce:author-group><ce:author><ce:given-name>Z.C.</ce:given-name><ce:surname>Li</ce:surname><ce:cross-ref refid="FN1"><ce:sup>∗</ce:sup></ce:cross-ref></ce:author><ce:affiliation><ce:textfn>Department of Applied Mathematics National Sun Yat-sen University, Kaohsiung, Taiwan 80424, R.O.C.</ce:textfn></ce:affiliation><ce:footnote id="FN1"><ce:label>∗</ce:label><ce:note-para>We are grateful to J. Guo for assistance in computer programming and data analysis in this paper.</ce:note-para></ce:footnote></ce:author-group><ce:author-group><ce:author><ce:given-name>C.Y.</ce:given-name><ce:surname>Suen</ce:surname><ce:cross-ref refid="FN1"><ce:sup>∗</ce:sup></ce:cross-ref></ce:author><ce:affiliation><ce:textfn>Centre for Pattern Recognition and Machine Intelligence, Concordia University, Suite GM-606 1455 de Maisonneuve Blvd. West, Montreal, Quebec H.3G IMS, Canada</ce:textfn></ce:affiliation></ce:author-group><ce:abstract><ce:section-title>Abstract</ce:section-title><ce:abstract-sec><ce:simple-para>A combining approach has been studied previously to integrate different parts of handwritten characters for their analysis and recognition. Perfect combinations, by which the characters can be identified with certainty, are important to pattern analysis and character recognition. However, a large number of possible combinations (e.g., 63 combinations for a character partitioned into six parts), also produce a lot of perfect combinations. Hence, it is necessary to determine which of them are most important. In this paper, we propose a methodology of finding the basic crucial combinations, and algorithms to compute them. Compared with perfect combinations, such basic crucial combinations are most significant to the character distinctiveness. Similarly, the largest confusion regions are also identified.</ce:simple-para><ce:simple-para>Experimental studies have also been conducted using the 89 most frequently used patterns of 36 alphanumeric handprints, to obtain their basic crucial combinations and largest confusion combinations. The results indicate that the ratio of the number of basic crucial combinations to perfect combinations is only 12.6%, and the ratio of the number of the largest confusion regions to the total confusion combinations is 15.6%.</ce:simple-para></ce:abstract-sec></ce:abstract><ce:keywords><ce:section-title>Keywords</ce:section-title><ce:keyword><ce:text>Character recognition</ce:text></ce:keyword><ce:keyword><ce:text>Handwritten characters</ce:text></ce:keyword><ce:keyword><ce:text>Handwritten recognition</ce:text></ce:keyword><ce:keyword><ce:text>Alphanumeric handprints</ce:text></ce:keyword><ce:keyword><ce:text>Regional decomposition method</ce:text></ce:keyword><ce:keyword><ce:text>Part combination</ce:text></ce:keyword><ce:keyword><ce:text>Crucial part</ce:text></ce:keyword><ce:keyword><ce:text>Perfect combinations</ce:text></ce:keyword><ce:keyword><ce:text>Crucial combinations</ce:text></ce:keyword><ce:keyword><ce:text>Confusion combinations</ce:text></ce:keyword><ce:keyword><ce:text>Largest confusion combinations</ce:text></ce:keyword></ce:keywords></head></converted-article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo><title>Crucial combinations of parts for handwritten alphanumeric characters</title></titleInfo><titleInfo type="alternative" contentType="CDATA"><title>Crucial combinations of parts for handwritten alphanumeric characters</title></titleInfo><name type="personal"><namePart type="given">Z.C.</namePart><namePart type="family">Li</namePart><affiliation>Department of Applied Mathematics National Sun Yat-sen University, Kaohsiung, Taiwan 80424, R.O.C.</affiliation><description>We are grateful to J. Guo for assistance in computer programming and data analysis in this paper.</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">C.Y.</namePart><namePart type="family">Suen</namePart><affiliation>Centre for Pattern Recognition and Machine Intelligence, Concordia University, Suite GM-606 1455 de Maisonneuve Blvd. West, Montreal, Quebec H.3G IMS, Canada</affiliation><description>We are grateful to J. Guo for assistance in computer programming and data analysis in this paper.</description><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="Full-length article"></genre><originInfo><publisher>ELSEVIER</publisher><dateIssued encoding="w3cdtf">2000</dateIssued><copyrightDate encoding="w3cdtf">2000</copyrightDate></originInfo><language><languageTerm type="code" authority="iso639-2b">eng</languageTerm><languageTerm type="code" authority="rfc3066">en</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">A combining approach has been studied previously to integrate different parts of handwritten characters for their analysis and recognition. Perfect combinations, by which the characters can be identified with certainty, are important to pattern analysis and character recognition. However, a large number of possible combinations (e.g., 63 combinations for a character partitioned into six parts), also produce a lot of perfect combinations. Hence, it is necessary to determine which of them are most important. In this paper, we propose a methodology of finding the basic crucial combinations, and algorithms to compute them. Compared with perfect combinations, such basic crucial combinations are most significant to the character distinctiveness. Similarly, the largest confusion regions are also identified. Experimental studies have also been conducted using the 89 most frequently used patterns of 36 alphanumeric handprints, to obtain their basic crucial combinations and largest confusion combinations. The results indicate that the ratio of the number of basic crucial combinations to perfect combinations is only 12.6%, and the ratio of the number of the largest confusion regions to the total confusion combinations is 15.6%.</abstract><note>This work was supported in part by National Sciences Council of Republic of China, by the Natural Sciences and Engineering Research Council of Canada, and by the Fonds pour la Formation de Chercheurs et l'Aide à la Recherche of Québec, the Ministère de l'Enseignement Superieur et de la Science.</note><subject><genre>Keywords</genre><topic>Character recognition</topic><topic>Handwritten characters</topic><topic>Handwritten recognition</topic><topic>Alphanumeric handprints</topic><topic>Regional decomposition method</topic><topic>Part combination</topic><topic>Crucial part</topic><topic>Perfect combinations</topic><topic>Crucial combinations</topic><topic>Confusion combinations</topic><topic>Largest confusion combinations</topic></subject><relatedItem type="host"><titleInfo><title>Mathematical and Computer Modelling</title></titleInfo><titleInfo type="abbreviated"><title>MCM</title></titleInfo><genre type="Journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">200004</dateIssued></originInfo><identifier type="ISSN">0895-7177</identifier><identifier type="PII">S0895-7177(00)X0095-7</identifier><part><date>200004</date><detail type="volume"><number>31</number><caption>vol.</caption></detail><detail type="issue"><number>8–9</number><caption>no.</caption></detail><extent unit="issue pages"><start>1</start><end>229</end></extent><extent unit="pages"><start>193</start><end>229</end></extent></part></relatedItem><identifier type="istex">4B8AED8224EEF6AF136BDD6F26F634D1EA68C213</identifier><identifier type="DOI">10.1016/S0895-7177(00)00065-0</identifier><identifier type="PII">S0895-7177(00)00065-0</identifier><recordInfo><recordContentSource>ELSEVIER</recordContentSource></recordInfo></mods></metadata><enrichments><istex:catWosTEI uri="https://api.istex.fr/document/4B8AED8224EEF6AF136BDD6F26F634D1EA68C213/enrichments/catWos"><teiHeader><profileDesc><textClass><classCode scheme="WOS">COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS</classCode><classCode scheme="WOS">COMPUTER SCIENCE, SOFTWARE ENGINEERING</classCode><classCode scheme="WOS">MATHEMATICS, APPLIED</classCode></textClass></profileDesc></teiHeader></istex:catWosTEI></enrichments></istex></record>Pour manipuler ce document sous Unix (Dilib)
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