An algebraic approach for morphological operations on 2D and 3D images
Identifieur interne : 000952 ( Istex/Corpus ); précédent : 000951; suivant : 000953An algebraic approach for morphological operations on 2D and 3D images
Auteurs : Prabir Bhattacharya ; Kai Qian ; Xun LuSource :
- Pattern Recognition [ 0031-3203 ] ; 1993.
Abstract
This paper describes an algebraic approach to morphological operations on 2D and 3D images. For 2D images, a matching algorithm based on mathematical morphology is given. For 3D images represented by voxels, algorithms are developed for the shape decomposition and thinning. The possible advantages of the algebraic approach are indicated by showing that a considerable speedup takes place (for large-sized templates) if the Fast Fourier Transform (FFT) is used to compute the convolutions.
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DOI: 10.1016/0031-3203(93)90176-W
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For 2D images, a matching algorithm based on mathematical morphology is given. For 3D images represented by voxels, algorithms are developed for the shape decomposition and thinning. The possible advantages of the algebraic approach are indicated by showing that a considerable speedup takes place (for large-sized templates) if the Fast Fourier Transform (FFT) is used to compute the convolutions.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>Prabir Bhattacharya</name></json:item><json:item><name>Kai Qian</name><affiliations><json:string>Department of Computer Science & Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588-0115, U.S.A.</json:string><json:string>†Present address: Department of Computer Science, Georgia Southwestern College, Americus, GA 31709, U.S.A.</json:string></affiliations></json:item><json:item><name>Xun Lu</name></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>Voxel representation</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Morphology</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Algebraic approach</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Polynomials</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>3D shape decomposition</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>3D thinning</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Fast Fourier Transform</value></json:item></subject><language><json:string>eng</json:string></language><abstract>This paper describes an algebraic approach to morphological operations on 2D and 3D images. For 2D images, a matching algorithm based on mathematical morphology is given. For 3D images represented by voxels, algorithms are developed for the shape decomposition and thinning. 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For 2D images, a matching algorithm based on mathematical morphology is given. For 3D images represented by voxels, algorithms are developed for the shape decomposition and thinning. 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The possible advantages of the algebraic approach are indicated by showing that a considerable speedup takes place (for large-sized templates) if the Fast Fourier Transform (FFT) is used to compute the convolutions.</abstract><subject><genre>Keywords</genre><topic>Voxel representation</topic><topic>Morphology</topic><topic>Algebraic approach</topic><topic>Polynomials</topic><topic>3D shape decomposition</topic><topic>3D thinning</topic><topic>Fast Fourier Transform</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">199312</dateIssued></originInfo><identifier type="ISSN">0031-3203</identifier><identifier type="PII">S0031-3203(00)X0227-0</identifier><part><date>199312</date><detail type="volume"><number>26</number><caption>vol.</caption></detail><detail type="issue"><number>12</number><caption>no.</caption></detail><extent unit="issue pages"><start>1739</start><end>1867</end></extent><extent unit="pages"><start>1785</start><end>1796</end></extent></part></relatedItem><identifier type="istex">C3B75502E3B7E65F42F13005B27C729831387D4A</identifier><identifier type="DOI">10.1016/0031-3203(93)90176-W</identifier><identifier type="PII">0031-3203(93)90176-W</identifier><recordInfo><recordContentSource>ELSEVIER</recordContentSource></recordInfo></mods></metadata><enrichments><istex:catWosTEI uri="https://api.istex.fr/document/C3B75502E3B7E65F42F13005B27C729831387D4A/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></enrichments></istex></record>Pour manipuler ce document sous Unix (Dilib)
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