Alignment-Based Recognition of Shape Outlines
We present a 2D shape recognition and classification method based on matching shape outlines. The correspondence between outlines (curves) is based on a notion of an alignment curve and on a measure of similarity between the intrinsic properties of the curve, namely, length and curvature, and is fou...
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| creator | Sebastian, Thomas B. Klein, Philip N. Kimia, Benjamin B. |
| description | We present a 2D shape recognition and classification method based on matching shape outlines. The correspondence between outlines (curves) is based on a notion of an alignment curve and on a measure of similarity between the intrinsic properties of the curve, namely, length and curvature, and is found by an efficient dynamic-programming method. The correspondence is used to find a similarity measure which is used in a recognition system. We explore the strengths and weaknesses of the outline-based representation by examining the effectiveness of the recognition system on a variety of examples. |
| doi_str_mv | 10.1007/3-540-45129-3_56 |
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The correspondence between outlines (curves) is based on a notion of an alignment curve and on a measure of similarity between the intrinsic properties of the curve, namely, length and curvature, and is found by an efficient dynamic-programming method. The correspondence is used to find a similarity measure which is used in a recognition system. We explore the strengths and weaknesses of the outline-based representation by examining the effectiveness of the recognition system on a variety of examples.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 9783540421207</identifier><identifier>ISBN: 3540421203</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 9783540451297</identifier><identifier>EISBN: 3540451293</identifier><identifier>DOI: 10.1007/3-540-45129-3_56</identifier><identifier>OCLC: 958523907</identifier><identifier>LCCallNum: QA76.76.A65</identifier><language>eng</language><publisher>Germany: Springer Berlin / Heidelberg</publisher><subject>Applied sciences ; Artificial intelligence ; Closed Curf ; Computer science; control theory; systems ; Curve Segment ; Edit Distance ; Exact sciences and technology ; Optimal Alignment ; Pattern recognition. Digital image processing. 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The correspondence between outlines (curves) is based on a notion of an alignment curve and on a measure of similarity between the intrinsic properties of the curve, namely, length and curvature, and is found by an efficient dynamic-programming method. The correspondence is used to find a similarity measure which is used in a recognition system. We explore the strengths and weaknesses of the outline-based representation by examining the effectiveness of the recognition system on a variety of examples.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Closed Curf</subject><subject>Computer science; control theory; systems</subject><subject>Curve Segment</subject><subject>Edit Distance</subject><subject>Exact sciences and technology</subject><subject>Optimal Alignment</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Shape Match</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540421207</isbn><isbn>3540421203</isbn><isbn>9783540451297</isbn><isbn>3540451293</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2001</creationdate><recordtype>book_chapter</recordtype><recordid>eNpFUMlOwzAQNauISu8ce-DqMvZ4iY-lYpMqVWI5W07slECalDg98Pe4i8Rc5mneIs0j5IbBlAHoO6RSABWScUPRSnVCxkbnmI77mz4lGVOMUURhzv45zjjoc5IBAqdGC7wkmZG55GhAX5FxjF-QBrmWWmeEzpp61a5DO9B7F4OfvIayW7X1UHftpKsmb59uEybL7dDUbYjX5KJyTQzj4x6Rj8eH9_kzXSyfXuazBS05N4oyYSqZK1fpwhtfssBkxb2rsDIFVwl6LIJixkulmOC-hJz7AoQShUYAjyNye8jduFi6pupdW9bRbvp67fpfy4CpXLIkmx5kMTHtKvS26LrvmHi7q9Cm2gTYfV07rJIBj7l997MNcbBh5yjT-71ryvTrEPpoETTXqK3iVjHAP6GVbIk</recordid><startdate>2001</startdate><enddate>2001</enddate><creator>Sebastian, Thomas B.</creator><creator>Klein, Philip N.</creator><creator>Kimia, Benjamin B.</creator><general>Springer Berlin / Heidelberg</general><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>FFUUA</scope><scope>IQODW</scope></search><sort><creationdate>2001</creationdate><title>Alignment-Based Recognition of Shape Outlines</title><author>Sebastian, Thomas B. ; Klein, Philip N. ; Kimia, Benjamin B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2296-149f586af7bd9dc1e15f2daf3f9b26f2dd3be619d566142dc082db0464b7300d3</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Closed Curf</topic><topic>Computer science; control theory; systems</topic><topic>Curve Segment</topic><topic>Edit Distance</topic><topic>Exact sciences and technology</topic><topic>Optimal Alignment</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Shape Match</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sebastian, Thomas B.</creatorcontrib><creatorcontrib>Klein, Philip N.</creatorcontrib><creatorcontrib>Kimia, Benjamin B.</creatorcontrib><collection>ProQuest Ebook Central - Book Chapters - Demo use only</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sebastian, Thomas B.</au><au>Klein, Philip N.</au><au>Kimia, Benjamin B.</au><au>Cordella, Luigi P</au><au>Arcelli, Carlo</au><au>Sanniti di Baja, Gabriella</au><au>Arcelli, Carlo</au><au>Cordella, Luigi P.</au><au>di Baja, Gabriella Sanniti</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>Alignment-Based Recognition of Shape Outlines</atitle><btitle>Lecture notes in computer science</btitle><seriestitle>Lecture Notes in Computer Science</seriestitle><date>2001</date><risdate>2001</risdate><volume>2059</volume><spage>606</spage><epage>618</epage><pages>606-618</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540421207</isbn><isbn>3540421203</isbn><eisbn>9783540451297</eisbn><eisbn>3540451293</eisbn><abstract>We present a 2D shape recognition and classification method based on matching shape outlines. The correspondence between outlines (curves) is based on a notion of an alignment curve and on a measure of similarity between the intrinsic properties of the curve, namely, length and curvature, and is found by an efficient dynamic-programming method. The correspondence is used to find a similarity measure which is used in a recognition system. We explore the strengths and weaknesses of the outline-based representation by examining the effectiveness of the recognition system on a variety of examples.</abstract><cop>Germany</cop><pub>Springer Berlin / Heidelberg</pub><doi>10.1007/3-540-45129-3_56</doi><oclcid>958523907</oclcid><tpages>13</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Lecture notes in computer science, 2001, Vol.2059, p.606-618 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_1016851 |
| source | Springer Books |
| subjects | Applied sciences Artificial intelligence Closed Curf Computer science control theory systems Curve Segment Edit Distance Exact sciences and technology Optimal Alignment Pattern recognition. Digital image processing. Computational geometry Shape Match |
| title | Alignment-Based Recognition of Shape Outlines |
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