Block decomposition and segmentation for fast Hough transform evaluation
Identifieur interne : 000895 ( Istex/Corpus ); précédent : 000894; suivant : 000896Block decomposition and segmentation for fast Hough transform evaluation
Auteurs : Stavros J. Perantonis ; Basilios Gatos ; Nikos PapamarkosSource :
- Pattern Recognition [ 0031-3203 ] ; 1997.
Abstract
The decomposition of binary images using rectangular blocks of foreground pixels as primitives is considered. Based on this type of decomposition, a fast method for evaluating the Hough transform is introduced. A complexity analysis of the proposed block Hough transform algorithm sets constraints on the complexity of algorithms used for block decomposition, so that the total decomposition and Hough transform application time is much less than the time consumed by the usual point Hough transform. Using this analysis, we propose two algorithms for the decomposition and segmentation of binary images into rectangular blocks. A combination of these methods leads to significant acceleration in the identification of linear features, which is demonstrated in various image processing experiments.
Url:
DOI: 10.1016/S0031-3203(98)00125-3
Links to Exploration step
ISTEX:430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FFLe document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title>Block decomposition and segmentation for fast Hough transform evaluation</title><author><name sortKey="Perantonis, Stavros J" sort="Perantonis, Stavros J" uniqKey="Perantonis S" first="Stavros J." last="Perantonis">Stavros J. Perantonis</name><affiliation><mods:affiliation>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</mods:affiliation></affiliation></author><author><name sortKey="Gatos, Basilios" sort="Gatos, Basilios" uniqKey="Gatos B" first="Basilios" last="Gatos">Basilios Gatos</name><affiliation><mods:affiliation>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</mods:affiliation></affiliation></author><author><name sortKey="Papamarkos, Nikos" sort="Papamarkos, Nikos" uniqKey="Papamarkos N" first="Nikos" last="Papamarkos">Nikos Papamarkos</name><affiliation><mods:affiliation>Electric Circuits Analysis Laboratory, Department of Electrical and Computer Engineering, Demokritus University of Thrace, 67100 Xanthi, Greece</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF</idno><date when="1999" year="1999">1999</date><idno type="doi">10.1016/S0031-3203(98)00125-3</idno><idno type="url">https://api.istex.fr/document/430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000895</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a">Block decomposition and segmentation for fast Hough transform evaluation</title><author><name sortKey="Perantonis, Stavros J" sort="Perantonis, Stavros J" uniqKey="Perantonis S" first="Stavros J." last="Perantonis">Stavros J. Perantonis</name><affiliation><mods:affiliation>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</mods:affiliation></affiliation></author><author><name sortKey="Gatos, Basilios" sort="Gatos, Basilios" uniqKey="Gatos B" first="Basilios" last="Gatos">Basilios Gatos</name><affiliation><mods:affiliation>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</mods:affiliation></affiliation></author><author><name sortKey="Papamarkos, Nikos" sort="Papamarkos, Nikos" uniqKey="Papamarkos N" first="Nikos" last="Papamarkos">Nikos Papamarkos</name><affiliation><mods:affiliation>Electric Circuits Analysis Laboratory, Department of Electrical and Computer Engineering, Demokritus University of Thrace, 67100 Xanthi, Greece</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Pattern Recognition</title><title level="j" type="abbrev">PR</title><idno type="ISSN">0031-3203</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1997">1997</date><biblScope unit="volume">32</biblScope><biblScope unit="issue">5</biblScope><biblScope unit="page" from="811">811</biblScope><biblScope unit="page" to="824">824</biblScope></imprint><idno type="ISSN">0031-3203</idno></series><idno type="istex">430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF</idno><idno type="DOI">10.1016/S0031-3203(98)00125-3</idno><idno type="PII">S0031-3203(98)00125-3</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0031-3203</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The decomposition of binary images using rectangular blocks of foreground pixels as primitives is considered. Based on this type of decomposition, a fast method for evaluating the Hough transform is introduced. A complexity analysis of the proposed block Hough transform algorithm sets constraints on the complexity of algorithms used for block decomposition, so that the total decomposition and Hough transform application time is much less than the time consumed by the usual point Hough transform. Using this analysis, we propose two algorithms for the decomposition and segmentation of binary images into rectangular blocks. A combination of these methods leads to significant acceleration in the identification of linear features, which is demonstrated in various image processing experiments.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>Stavros J. Perantonis</name><affiliations><json:string>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</json:string></affiliations></json:item><json:item><name>Basilios Gatos</name><affiliations><json:string>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</json:string></affiliations></json:item><json:item><name>Nikos Papamarkos</name><affiliations><json:string>Electric Circuits Analysis Laboratory, Department of Electrical and Computer Engineering, Demokritus University of Thrace, 67100 Xanthi, Greece</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>Fast Hough transform</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Image decomposition</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Segmentation</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Skew detection</value></json:item></subject><language><json:string>eng</json:string></language><abstract>The decomposition of binary images using rectangular blocks of foreground pixels as primitives is considered. Based on this type of decomposition, a fast method for evaluating the Hough transform is introduced. A complexity analysis of the proposed block Hough transform algorithm sets constraints on the complexity of algorithms used for block decomposition, so that the total decomposition and Hough transform application time is much less than the time consumed by the usual point Hough transform. Using this analysis, we propose two algorithms for the decomposition and segmentation of binary images into rectangular blocks. A combination of these methods leads to significant acceleration in the identification of linear features, which is demonstrated in various image processing experiments.</abstract><qualityIndicators><score>6.392</score><pdfVersion>1.2</pdfVersion><pdfPageSize>501 x 713 pts</pdfPageSize><refBibsNative>false</refBibsNative><keywordCount>4</keywordCount><abstractCharCount>798</abstractCharCount><pdfWordCount>6979</pdfWordCount><pdfCharCount>38621</pdfCharCount><pdfPageCount>14</pdfPageCount><abstractWordCount>116</abstractWordCount></qualityIndicators><title>Block decomposition and segmentation for fast Hough transform evaluation</title><pii><json:string>S0031-3203(98)00125-3</json:string></pii><genre><json:string>research-article</json:string></genre><host><volume>32</volume><pii><json:string>S0031-3203(00)X0052-0</json:string></pii><pages><last>824</last><first>811</first></pages><issn><json:string>0031-3203</json:string></issn><issue>5</issue><genre><json:string>Journal</json:string></genre><language><json:string>unknown</json:string></language><title>Pattern Recognition</title><publicationDate>1999</publicationDate></host><categories><wos><json:string>COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE</json:string><json:string>ENGINEERING, ELECTRICAL & ELECTRONIC</json:string></wos></categories><publicationDate>1997</publicationDate><copyrightDate>1999</copyrightDate><doi><json:string>10.1016/S0031-3203(98)00125-3</json:string></doi><id>430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF</id><fulltext><json:item><original>true</original><mimetype>application/pdf</mimetype><extension>pdf</extension><uri>https://api.istex.fr/document/430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF/fulltext/pdf</uri></json:item><json:item><original>false</original><mimetype>application/zip</mimetype><extension>zip</extension><uri>https://api.istex.fr/document/430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a">Block decomposition and segmentation for fast Hough transform evaluation</title><respStmt xml:id="ISTEX-API" resp="Références bibliographiques récupérées via GROBID" name="ISTEX-API (INIST-CNRS)"></respStmt></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>ELSEVIER</publisher><availability><p>ELSEVIER</p></availability><date>1999</date></publicationStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a">Block decomposition and segmentation for fast Hough transform evaluation</title><author><persName><forename type="first">Stavros J.</forename><surname>Perantonis</surname></persName><note type="correspondence"><p>Corresponding author</p></note><affiliation>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</affiliation></author><author><persName><forename type="first">Basilios</forename><surname>Gatos</surname></persName><affiliation>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</affiliation></author><author><persName><forename type="first">Nikos</forename><surname>Papamarkos</surname></persName><affiliation>Electric Circuits Analysis Laboratory, Department of Electrical and Computer Engineering, Demokritus University of Thrace, 67100 Xanthi, Greece</affiliation></author></analytic><monogr><title level="j">Pattern Recognition</title><title level="j" type="abbrev">PR</title><idno type="pISSN">0031-3203</idno><idno type="PII">S0031-3203(00)X0052-0</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1997"></date><biblScope unit="volume">32</biblScope><biblScope unit="issue">5</biblScope><biblScope unit="page" from="811">811</biblScope><biblScope unit="page" to="824">824</biblScope></imprint></monogr><idno type="istex">430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF</idno><idno type="DOI">10.1016/S0031-3203(98)00125-3</idno><idno type="PII">S0031-3203(98)00125-3</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>1999</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>The decomposition of binary images using rectangular blocks of foreground pixels as primitives is considered. Based on this type of decomposition, a fast method for evaluating the Hough transform is introduced. A complexity analysis of the proposed block Hough transform algorithm sets constraints on the complexity of algorithms used for block decomposition, so that the total decomposition and Hough transform application time is much less than the time consumed by the usual point Hough transform. Using this analysis, we propose two algorithms for the decomposition and segmentation of binary images into rectangular blocks. A combination of these methods leads to significant acceleration in the identification of linear features, which is demonstrated in various image processing experiments.</p></abstract><textClass><keywords scheme="keyword"><list><head>Keywords</head><item><term>Fast Hough transform</term></item><item><term>Image decomposition</term></item><item><term>Segmentation</term></item><item><term>Skew detection</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="1997-10-16">Received</change><change when="1998-06-01">Modified</change><change when="1997">Published</change><change xml:id="refBibs-istex" who="#ISTEX-API" when="2016-3-5">References added</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><original>false</original><mimetype>text/plain</mimetype><extension>txt</extension><uri>https://api.istex.fr/document/430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Elsevier converted-article found"><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>PR</jid><aid>949</aid><ce:pii>S0031-3203(98)00125-3</ce:pii><ce:doi>10.1016/S0031-3203(98)00125-3</ce:doi><ce:copyright type="society" year="1999">Pattern Recognition Society</ce:copyright></item-info><head><ce:title>Block decomposition and segmentation for fast Hough transform evaluation</ce:title><ce:author-group><ce:author><ce:given-name>Stavros J.</ce:given-name><ce:surname>Perantonis</ce:surname><ce:cross-ref refid="ORFA"><ce:sup>a</ce:sup></ce:cross-ref><ce:cross-ref refid="COR1">*</ce:cross-ref></ce:author><ce:author><ce:given-name>Basilios</ce:given-name><ce:surname>Gatos</ce:surname><ce:cross-ref refid="ORFA"><ce:sup>a</ce:sup></ce:cross-ref><ce:cross-ref refid="ORFB"><ce:sup>b</ce:sup></ce:cross-ref></ce:author><ce:author><ce:given-name>Nikos</ce:given-name><ce:surname>Papamarkos</ce:surname><ce:cross-ref refid="ORFB"><ce:sup>b</ce:sup></ce:cross-ref></ce:author><ce:affiliation id="ORFA"><ce:label>a</ce:label><ce:textfn>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</ce:textfn></ce:affiliation><ce:affiliation id="ORFB"><ce:label>b</ce:label><ce:textfn>Electric Circuits Analysis Laboratory, Department of Electrical and Computer Engineering, Demokritus University of Thrace, 67100 Xanthi, Greece</ce:textfn></ce:affiliation><ce:correspondence id="COR1"><ce:label>*</ce:label><ce:text>Corresponding author</ce:text></ce:correspondence></ce:author-group><ce:date-received day="16" month="10" year="1997"></ce:date-received><ce:date-revised day="1" month="6" year="1998"></ce:date-revised><ce:abstract><ce:section-title>Abstract</ce:section-title><ce:abstract-sec><ce:simple-para>The decomposition of binary images using rectangular blocks of foreground pixels as primitives is considered. Based on this type of decomposition, a fast method for evaluating the Hough transform is introduced. A complexity analysis of the proposed block Hough transform algorithm sets constraints on the complexity of algorithms used for block decomposition, so that the total decomposition and Hough transform application time is much less than the time consumed by the usual point Hough transform. Using this analysis, we propose two algorithms for the decomposition and segmentation of binary images into rectangular blocks. A combination of these methods leads to significant acceleration in the identification of linear features, which is demonstrated in various image processing experiments.</ce:simple-para></ce:abstract-sec></ce:abstract><ce:keywords><ce:section-title>Keywords</ce:section-title><ce:keyword><ce:text>Fast Hough transform</ce:text></ce:keyword><ce:keyword><ce:text>Image decomposition</ce:text></ce:keyword><ce:keyword><ce:text>Segmentation</ce:text></ce:keyword><ce:keyword><ce:text>Skew detection</ce:text></ce:keyword></ce:keywords></head></converted-article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo><title>Block decomposition and segmentation for fast Hough transform evaluation</title></titleInfo><titleInfo type="alternative" contentType="CDATA"><title>Block decomposition and segmentation for fast Hough transform evaluation</title></titleInfo><name type="personal"><namePart type="given">Stavros J.</namePart><namePart type="family">Perantonis</namePart><affiliation>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</affiliation><description>Corresponding author</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Basilios</namePart><namePart type="family">Gatos</namePart><affiliation>Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 153 10 Aghia Paraskevi, Greece</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Nikos</namePart><namePart type="family">Papamarkos</namePart><affiliation>Electric Circuits Analysis Laboratory, Department of Electrical and Computer Engineering, Demokritus University of Thrace, 67100 Xanthi, Greece</affiliation><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">1997</dateIssued><dateCaptured encoding="w3cdtf">1997-10-16</dateCaptured><dateModified encoding="w3cdtf">1998-06-01</dateModified><copyrightDate encoding="w3cdtf">1999</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">The decomposition of binary images using rectangular blocks of foreground pixels as primitives is considered. Based on this type of decomposition, a fast method for evaluating the Hough transform is introduced. A complexity analysis of the proposed block Hough transform algorithm sets constraints on the complexity of algorithms used for block decomposition, so that the total decomposition and Hough transform application time is much less than the time consumed by the usual point Hough transform. Using this analysis, we propose two algorithms for the decomposition and segmentation of binary images into rectangular blocks. A combination of these methods leads to significant acceleration in the identification of linear features, which is demonstrated in various image processing experiments.</abstract><subject><genre>Keywords</genre><topic>Fast Hough transform</topic><topic>Image decomposition</topic><topic>Segmentation</topic><topic>Skew detection</topic></subject><relatedItem type="host"><titleInfo><title>Pattern Recognition</title></titleInfo><titleInfo type="abbreviated"><title>PR</title></titleInfo><genre type="Journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">199905</dateIssued></originInfo><identifier type="ISSN">0031-3203</identifier><identifier type="PII">S0031-3203(00)X0052-0</identifier><part><date>199905</date><detail type="volume"><number>32</number><caption>vol.</caption></detail><detail type="issue"><number>5</number><caption>no.</caption></detail><extent unit="issue pages"><start>715</start><end>906</end></extent><extent unit="pages"><start>811</start><end>824</end></extent></part></relatedItem><identifier type="istex">430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF</identifier><identifier type="DOI">10.1016/S0031-3203(98)00125-3</identifier><identifier type="PII">S0031-3203(98)00125-3</identifier><accessCondition type="use and reproduction" contentType="">© 1999Pattern Recognition Society</accessCondition><recordInfo><recordContentSource>ELSEVIER</recordContentSource><recordOrigin>Pattern Recognition Society, ©1999</recordOrigin></recordInfo></mods></metadata><enrichments><istex:catWosTEI uri="https://api.istex.fr/document/430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF/enrichments/catWos"><teiHeader><profileDesc><textClass><classCode scheme="WOS">COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE</classCode><classCode scheme="WOS">ENGINEERING, ELECTRICAL & ELECTRONIC</classCode></textClass></profileDesc></teiHeader></istex:catWosTEI><istex:refBibTEI uri="https://api.istex.fr/document/430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF/enrichments/refBib"><teiHeader></teiHeader><text><front></front><body></body><back><listBibl><biblStruct><monogr><title level="m" type="main">Image Processing, Analysis and Machine Vision</title><author><persName><forename type="first">M</forename><surname>Sonka</surname></persName></author><author><persName><forename type="first">V</forename><surname>Hlavac</surname></persName></author><author><persName><forename type="first">R</forename><surname>Boyle</surname></persName></author><imprint><date type="published" when="1993"></date><publisher>Chapman & Hall</publisher><pubPlace>London</pubPlace></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">A general approach to moment calculation for polygons and line segments</title><author><persName><forename type="first">M</forename><forename type="middle">H</forename><surname>Singer</surname></persName></author></analytic><monogr><title level="j">Pattern Recognition</title><imprint><biblScope unit="volume">26</biblScope><date type="published" when="1993"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">Shape decomposition and representation using a recursive morphological opera-tion</title><author><persName><forename type="first">D</forename><surname>Wang</surname></persName></author><author><persName><forename type="first">V</forename><surname>Haese-Coat</surname></persName></author><author><persName><forename type="first">J</forename><surname>Ronsin</surname></persName></author></analytic><monogr><title level="j">Pattern Recognition</title><imprint><biblScope unit="volume">28</biblScope><biblScope unit="page" from="1783" to="1792"></biblScope><date type="published" when="1995"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">Use of the Hough transform to detect lines and curves in pictures</title><author><persName><forename type="first">R</forename><forename type="middle">D</forename><surname>Duda</surname></persName></author><author><persName><forename type="first">P</forename><forename type="middle">E</forename><surname>Hart</surname></persName></author></analytic><monogr><title level="j">Commun. ACM</title><imprint><biblScope unit="volume">15</biblScope><biblScope unit="page" from="11" to="15"></biblScope><date type="published" when="1972"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">Generalizing the Hough transform to detect arbitrary shapes</title><author><persName><forename type="first">D</forename><forename type="middle">H</forename><surname>Ballard</surname></persName></author></analytic><monogr><title level="j">Pattern Recognition</title><imprint><biblScope unit="volume">13</biblScope><biblScope unit="page" from="111" to="122"></biblScope><date type="published" when="1981"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">Viewer independent shape rec-ognition</title><author><persName><forename type="first">D</forename><forename type="middle">H</forename><surname>Ballard</surname></persName></author><author><persName><forename type="first">D</forename><surname>Sabbah</surname></persName></author></analytic><monogr><title level="j">IEEE Trans. Pattern Anal. Machine Intelligence</title><imprint><biblScope unit="volume">5</biblScope><biblScope unit="page" from="653" to="659"></biblScope><date type="published" when="1983"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">SDFS: a new strategy for the recogni-tion of object using range data</title><author><persName><forename type="first">X</forename><surname>Lin</surname></persName></author><author><persName><forename type="first">W</forename><forename type="middle">G</forename><surname>Wee</surname></persName></author></analytic><monogr><title level="m">Proc. Int. Conf. Robotics and Automation</title><meeting>. Int. Conf. Robotics and Automation</meeting><imprint><date type="published" when="1986"></date><biblScope unit="page" from="770" to="775"></biblScope></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">Fast Hough transform on a mesh connected processor array</title><author><persName><forename type="first">C</forename><forename type="middle">S</forename><surname>Kannan</surname></persName></author><author><persName><forename type="first">H</forename><forename type="middle">Y H</forename><surname>Chuang</surname></persName></author></analytic><monogr><title level="j">Inform. Process. Lett</title><imprint><biblScope unit="page" from="33" to="243"></biblScope><date type="published" when="1990"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">An efficient Hough transform algorithm on SIMD hypercube</title><author><persName><forename type="first">H</forename><forename type="middle">Y H</forename><surname>Chuang</surname></persName></author><author><persName><forename type="first">C</forename><surname>Ling</surname></persName></author></analytic><monogr><title level="m">Proc. Intern. Conf. on Parallel and Distributed Systems</title><meeting>. Intern. Conf. on Parallel and Distributed Systems<address>Hsinchu, Taiwan</address></meeting><imprint><date type="published" when="1994"></date><biblScope unit="page" from="236" to="241"></biblScope></imprint></monogr></biblStruct><biblStruct><monogr><title level="m" type="main">Computing the Hough transform on reconfigurable meshes, Image Vision Com-put</title><author><persName><forename type="first">S</forename><surname>Olariu</surname></persName></author><author><persName><forename type="first">J</forename><forename type="middle">L</forename><surname>Schwing</surname></persName></author><author><persName><forename type="first">J</forename><surname>Zhang</surname></persName></author><imprint><date type="published" when="1993"></date><biblScope unit="page" from="623" to="628"></biblScope></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">A fast digital radon trans-form — an efficient means for evaluating the Hough trans-form</title><author><persName><forename type="first">W</forename><forename type="middle">A</forename><surname>Go¨</surname></persName></author><author><persName><forename type="first">H</forename><forename type="middle">J</forename><surname>Druckmuï</surname></persName></author></analytic><monogr><title level="j">Pattern Recognition</title><imprint><biblScope unit="page">28</biblScope><date type="published" when="1995"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">Detection of line segments using a fast dynamic Hough transform</title><author><persName><forename type="first">L</forename><surname>Yang</surname></persName></author><author><persName><forename type="first">Z</forename><surname>He</surname></persName></author></analytic><monogr><title level="m">Proc. IEEE Int. Symp on Circuits and Systems</title><meeting>. IEEE Int. Symp on Circuits and Systems<address>Chicago, IL, USA</address></meeting><imprint><date type="published" when="1993"></date><biblScope unit="page" from="543" to="546"></biblScope></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">Fast Hough transform: a hierarchical approach, Comp. Vision Graph</title><author><persName><forename type="first">M</forename><forename type="middle">A</forename><surname>Li</surname></persName></author><author><persName><forename type="first">R</forename><forename type="middle">J</forename><surname>Lavin</surname></persName></author><author><persName><surname>Lemaster</surname></persName></author></analytic><monogr><title level="j">Image Process</title><imprint><biblScope unit="volume">36</biblScope><biblScope unit="page" from="139" to="161"></biblScope><date type="published" when="1986"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">A modified Hough transform: knowledge-based boundary conver-gence algorithm</title><author><persName><forename type="first">L</forename><forename type="middle">T S</forename><surname>Lam</surname></persName></author><author><persName><forename type="first">W</forename><forename type="middle">C Y</forename><surname>Lam</surname></persName></author><author><persName><forename type="first">D</forename><forename type="middle">N K</forename><surname>Leung</surname></persName></author></analytic><monogr><title level="m">Proc. 2nd Int. Conf. Image Processing</title><meeting>. 2nd Int. Conf. Image essing<address>Singapore</address></meeting><imprint><date type="published" when="1992"></date><biblScope unit="page" from="226" to="230"></biblScope></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">A fast Hough transform for segment detection</title><author><persName><forename type="first">N</forename><surname>Guil</surname></persName></author><author><persName><forename type="first">J</forename><surname>Villalba</surname></persName></author><author><persName><forename type="first">E</forename><forename type="middle">L</forename><surname>Zapata</surname></persName></author></analytic><monogr><title level="j">IEEE Trans. Image Process</title><imprint><biblScope unit="volume">4</biblScope><biblScope unit="page" from="1541" to="1548"></biblScope><date type="published" when="1995"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">Fast generalized Hough transform</title><author><persName><forename type="first">S</forename><forename type="middle">C</forename><surname>Jeng</surname></persName></author><author><persName><forename type="first">W</forename><forename type="middle">H</forename><surname>Tsai</surname></persName></author></analytic><monogr><title level="j">Pattern Recognition Lett</title><imprint><biblScope unit="page" from="11" to="725"></biblScope><date type="published" when="1990"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">A fast Hough transform for inspecting accurate needle-type meter gauges</title><author><persName><forename type="first">L</forename><surname>Ke-Qing</surname></persName></author><author><persName><forename type="first">T</forename><surname>Qi</surname></persName></author></analytic><monogr><title level="m">Proc. IAPR Workshop on Computer Vision</title><meeting>. IAPR Workshop on Computer Vision</meeting><imprint><date type="published" when="1988"></date><biblScope unit="page" from="195" to="198"></biblScope></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">Document analysis system</title><author><persName><forename type="first">K</forename><forename type="middle">Y</forename><surname>Wong</surname></persName></author><author><persName><forename type="first">R</forename><forename type="middle">G</forename><surname>Casey</surname></persName></author><author><persName><forename type="first">F</forename><forename type="middle">M</forename><surname>Wahl</surname></persName></author></analytic><monogr><title level="j">IBM J. Res. Devel</title><imprint><biblScope unit="volume">26</biblScope><biblScope unit="page" from="647" to="656"></biblScope><date type="published" when="1982"></date></imprint></monogr></biblStruct><biblStruct><monogr><title level="m" type="main">Block segmentation and text extraction in mixed text/image documents, Com-put. Graphics Image Process</title><author><persName><forename type="first">F</forename><forename type="middle">M</forename><surname>Wahl</surname></persName></author><author><persName><forename type="first">K</forename><forename type="middle">Y</forename><surname>Wong</surname></persName></author><author><persName><forename type="first">R</forename><forename type="middle">G</forename><surname>Casey</surname></persName></author><imprint><date type="published" when="1982"></date><biblScope unit="page" from="20" to="375"></biblScope></imprint></monogr></biblStruct><biblStruct><monogr><title level="m" type="main">Classification of newspaper image blocks using texture analysis, Computer Vision Graphics Image Process</title><author><persName><forename type="first">D</forename><surname>Wang</surname></persName></author><author><persName><forename type="first">S</forename><forename type="middle">N</forename><surname>Shihari</surname></persName></author><imprint><date type="published" when="1989"></date><biblScope unit="page" from="47" to="327"></biblScope></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">A robust and fast skew detection algo-rithm for generic documents</title><author><persName><forename type="first">B</forename><surname>Yu</surname></persName></author><author><persName><forename type="first">A</forename><forename type="middle">K</forename><surname>Jain</surname></persName></author></analytic><monogr><title level="j">Pattern Recognition</title><imprint><biblScope unit="page" from="29" to="1599"></biblScope><date type="published" when="1996"></date></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">Automated page ori-entation and skew angle detection for binary document images</title><author><persName><forename type="first">D</forename><forename type="middle">S</forename><surname>Le</surname></persName></author><author><persName><forename type="first">G</forename><forename type="middle">R</forename><surname>Thoma</surname></persName></author><author><persName><forename type="first">H</forename><surname>Wechsler</surname></persName></author></analytic><monogr><title level="j">Pattern Recognition</title><imprint><biblScope unit="page" from="27" to="1325"></biblScope><date type="published" when="1994"></date></imprint></monogr></biblStruct><biblStruct><monogr><title level="m" type="main">Skew correction of document images using inter-line cross-correlation, CVGIP: Graphical Models Image Process</title><author><persName><forename type="first">H</forename><surname>Yan</surname></persName></author><imprint><date type="published" when="1993"></date><biblScope unit="page" from="55" to="538"></biblScope></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">A document skew detection method using run-length encoding and the Hough transform</title><author><persName><forename type="first">S</forename><forename type="middle">C</forename><surname>Hinds</surname></persName></author><author><persName><forename type="first">J</forename><forename type="middle">L</forename><surname>Fisher</surname></persName></author><author><persName><forename type="first">D</forename><forename type="middle">P</forename><surname>Amato</surname></persName></author></analytic><monogr><title level="m">Proc. 10th Int. Conf. on Pattern Recog-nition 1990</title><meeting>. 10th Int. Conf. on Pattern Recog-nition 1990</meeting><imprint><biblScope unit="page" from="464" to="468"></biblScope></imprint></monogr></biblStruct><biblStruct><analytic><title level="a" type="main">He received his Diploma Degree in Physics from the University of Athens in 1984 His research interests involve image processing as well as the theory and applications of neural networks. Dr. Perantonis has authored or coauthored more than 60 publications in journals, book chapters and international conference proceedings. He has also acted as principal researcher or participated in numerous national or EU funded projects About the Author—BASILIOS GATOS was born in Athens, Greece, in 1967. He received his Electrical Engineering Diploma in 1992, and his Ph.D. degree inDemokritos'', where he worked till 1996. Dr. Gatos is currently working at Lambrakis Press S.A. in the field of digital preservation of old newspapers. His main research interests are in image processing and document image analysis, OCR and pattern recognition. He has 15 publications in journals and international conference proceedings and has participated in three research programs funded by the European community. Dr. Gatos is a member of the Technical Chamber of Greece. About the Author—NIKOS PAPAMARKOS was born in Alexandroupoli, Greece, in 1956. He received his Diploma Degree in Electrical and Mechanical Engineering from the</title><author><persName><forename type="first">S</forename><forename type="middle">N</forename><surname>Shihari</surname></persName></author><author><persName><forename type="first">V</forename><surname>Govindaraju</surname></persName></author></analytic><monogr><title level="m">Analysis of textual images using the Hough transform, Mach. Vis. Appl. 2 (1989) 141—153. About the Author—STAVROS J. PERANTONIS was born in Athens, Greece 1993 he was awarded a scholarship from the Institute of Informatics and Telecommunications 1979 and the Ph His current research interests are in digital signal processing, filter design, optimization algorithms, image processing, pattern recognition and computer vision</title><meeting><address>Athens, Greece ; Thessaloniki, Greece ; USA</address></meeting><imprint><date type="published" when="1960"></date></imprint></monogr><note>from. 1990 to 1996 Assistant Professor in the Democritus University of Thrace where he is currently Associate Professor since 1996. During 1987 and 1992 he has also served as a Visiting Research Associate at the Georgia Institute of Technology. Dr. Nikos Papamarkos is a member of IEEE and a member of the Greek Technical Chamber</note></biblStruct></listBibl></back></text></istex:refBibTEI></enrichments><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/OcrV1/Data/Istex/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000895 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Istex/Corpus/biblio.hfd -nk 000895 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Ticri/CIDE
|area= OcrV1
|flux= Istex
|étape= Corpus
|type= RBID
|clé= ISTEX:430B389E95FB62F8B2F4ED3EDA5234AB63BAA7FF
|texte= Block decomposition and segmentation for fast Hough transform evaluation
}}
| This area was generated with Dilib version V0.6.32. |  |