OcrV1, PascalFrancis, Curation, bibRecord, 000951

Search technique for pattern recognition using relative distances

Identifieur interne : 000951 ( PascalFrancis/Curation ); précédent : 000950; suivant : 000952

Search technique for pattern recognition using relative distances

Auteurs : T. E. Portegys [États-Unis]

Source :

IEEE Transactions on Pattern Analysis and Machine Intelligence [ 0162-8828 ] ; 1995.

RBID : Pascal:95-0527484

Descripteurs français

Pascal (Inist)
- Application, Reconnaissance optique caractère, Algorithme, Fonction récursive, Structure donnée, Calcul, Reconnaissance forme, Théorie.

English descriptors

KwdEn :
- Algorithms, Application, Calculations, Data structures, Distance metric, NIST digit samples, Nearest neighbor, Optical character recognition, Pattern insertion, Pattern recognition, Pattern searching, Recursive functions, Theory.

Abstract

A technique for creating and searching a tree of patterns using relative distances is presented. The search is conducted to find patterns which are nearest neighbors of a given test pattern. The structure of the tree is such that the search time is proportional to the distance between the test pattern and its nearest neighbor, which suggests the anomalous possibility that a larger tree, which can be expected on average to contain closer neighbors, can be searched faster than a smaller tree. The technique has been used to recognize OCR digit samples derived from NIST data at an accuracy rate of 97% using a tree of 7,000 patterns.

A01	`01`	`1`		`@0 0162-8828`
A02	`01`			`@0 ITPIDJ`
A03		`1`		`@0 IEEE Trans Pattern Anal Mach Intell`
A05				`@2 17`
A06				`@2 9`
A08	`01`	`1`	`ENG`	`@1 Search technique for pattern recognition using relative distances`
A11	`01`	`1`		`@1 PORTEGYS (T. E.)`
A14	`01`			`@1 AT&T Bell Lab @2 Naperville IL @3 USA @Z 1 aut.`
A20				`@1 910-914`
A21				`@1 1995`
A23	`01`			`@0 ENG`
A43	`01`			`@1 INIST @2 222 T`
A44				`@0 A100`
A45				`@0 12 Refs.`
A47	`01`	`1`		`@0 95-0527484`
A60				`@1 P`
A61				`@0 A`
A64	`01`	`1`		`@0 IEEE Transactions on Pattern Analysis and Machine Intelligence`
A66	`01`			`@0 USA`
C01	`01`		`ENG`	@0 A technique for creating and searching a tree of patterns using relative distances is presented. The search is conducted to find patterns which are nearest neighbors of a given test pattern. The structure of the tree is such that the search time is proportional to the distance between the test pattern and its nearest neighbor, which suggests the anomalous possibility that a larger tree, which can be expected on average to contain closer neighbors, can be searched faster than a smaller tree. The technique has been used to recognize OCR digit samples derived from NIST data at an accuracy rate of 97% using a tree of 7,000 patterns.
C02	`01`	`1`		`@0 001D02C`
C02	`02`	`1`		`@0 001D02A`
C02	`03`	`1`		`@0 001D02B07B`
C02	`04`	`1`		`@0 001A02I01`
C03	`01`	`1`	`ENG`	`@0 Nearest neighbor @4 INC`
C03	`02`	`1`	`ENG`	`@0 Distance metric @4 INC`
C03	`03`	`1`	`ENG`	`@0 NIST digit samples @4 INC`
C03	`04`	`1`	`ENG`	`@0 Pattern insertion @4 INC`
C03	`05`	`1`	`ENG`	`@0 Pattern searching @4 INC`
C03	`06`	`X`	`FRE`	`@0 Application`
C03	`06`	`X`	`ENG`	`@0 Application`
C03	`06`	`X`	`GER`	`@0 Anwendung`
C03	`06`	`X`	`SPA`	`@0 Aplicación`
C03	`07`	`1`	`FRE`	`@0 Reconnaissance optique caractère`
C03	`07`	`1`	`ENG`	`@0 Optical character recognition`
C03	`08`	`1`	`FRE`	`@0 Algorithme`
C03	`08`	`1`	`ENG`	`@0 Algorithms`
C03	`09`	`1`	`FRE`	`@0 Fonction récursive`
C03	`09`	`1`	`ENG`	`@0 Recursive functions`
C03	`10`	`1`	`FRE`	`@0 Structure donnée`
C03	`10`	`1`	`ENG`	`@0 Data structures`
C03	`11`	`1`	`FRE`	`@0 Calcul`
C03	`11`	`1`	`ENG`	`@0 Calculations`
C03	`12`	`1`	`FRE`	`@0 Reconnaissance forme @3 P`
C03	`12`	`1`	`ENG`	`@0 Pattern recognition @3 P`
C03	`13`	`1`	`FRE`	`@0 Théorie`
C03	`13`	`1`	`ENG`	`@0 Theory`
N21				`@1 302`

Links toward previous steps (curation, corpus...)

to stream PascalFrancis, to step Corpus: Pour aller vers cette notice dans l'étape Curation :000A48

Links to Exploration step

Pascal:95-0527484

Le document en format XML

<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Search technique for pattern recognition using relative distances</title>
<author><name sortKey="Portegys, T E" sort="Portegys, T E" uniqKey="Portegys T" first="T. E." last="Portegys">T. E. Portegys</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>AT&T Bell Lab</s1>
<s2>Naperville IL</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">95-0527484</idno>
<date when="1995">1995</date>
<idno type="stanalyst">PASCAL 95-0527484 EI</idno>
<idno type="RBID">Pascal:95-0527484</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">000A48</idno>
<idno type="wicri:Area/PascalFrancis/Curation">000951</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Search technique for pattern recognition using relative distances</title>
<author><name sortKey="Portegys, T E" sort="Portegys, T E" uniqKey="Portegys T" first="T. E." last="Portegys">T. E. Portegys</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>AT&T Bell Lab</s1>
<s2>Naperville IL</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">IEEE Transactions on Pattern Analysis and Machine Intelligence</title>
<title level="j" type="abbreviated">IEEE Trans Pattern Anal Mach Intell</title>
<idno type="ISSN">0162-8828</idno>
<imprint><date when="1995">1995</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">IEEE Transactions on Pattern Analysis and Machine Intelligence</title>
<title level="j" type="abbreviated">IEEE Trans Pattern Anal Mach Intell</title>
<idno type="ISSN">0162-8828</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term>
<term>Application</term>
<term>Calculations</term>
<term>Data structures</term>
<term>Distance metric</term>
<term>NIST digit samples</term>
<term>Nearest neighbor</term>
<term>Optical character recognition</term>
<term>Pattern insertion</term>
<term>Pattern recognition</term>
<term>Pattern searching</term>
<term>Recursive functions</term>
<term>Theory</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Application</term>
<term>Reconnaissance optique caractère</term>
<term>Algorithme</term>
<term>Fonction récursive</term>
<term>Structure donnée</term>
<term>Calcul</term>
<term>Reconnaissance forme</term>
<term>Théorie</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">A technique for creating and searching a tree of patterns using relative  distances is presented.  The search is conducted to find patterns which are nearest neighbors of a given test pattern.  The structure of the tree is such that the search time is proportional to the distance between the test pattern and its nearest neighbor, which suggests the anomalous possibility that a larger tree, which can be expected on average to contain closer neighbors, can be searched faster than a smaller tree.  The technique has been used to recognize OCR digit samples derived from NIST data at an accuracy rate of 97% using a tree of 7,000 patterns.</div>
</front>
</TEI>
<inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>0162-8828</s0>
</fA01>
<fA02 i1="01"><s0>ITPIDJ</s0>
</fA02>
<fA03 i2="1"><s0>IEEE Trans Pattern Anal Mach Intell</s0>
</fA03>
<fA05><s2>17</s2>
</fA05>
<fA06><s2>9</s2>
</fA06>
<fA08 i1="01" i2="1" l="ENG"><s1>Search technique for pattern recognition using relative distances</s1>
</fA08>
<fA11 i1="01" i2="1"><s1>PORTEGYS (T. E.)</s1>
</fA11>
<fA14 i1="01"><s1>AT&T Bell Lab</s1>
<s2>Naperville IL</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
</fA14>
<fA20><s1>910-914</s1>
</fA20>
<fA21><s1>1995</s1>
</fA21>
<fA23 i1="01"><s0>ENG</s0>
</fA23>
<fA43 i1="01"><s1>INIST</s1>
<s2>222 T</s2>
</fA43>
<fA44><s0>A100</s0>
</fA44>
<fA45><s0>12 Refs.</s0>
</fA45>
<fA47 i1="01" i2="1"><s0>95-0527484</s0>
</fA47>
<fA60><s1>P</s1>
</fA60>
<fA61><s0>A</s0>
</fA61>
<fA64 i1="01" i2="1"><s0>IEEE Transactions on Pattern Analysis and Machine Intelligence</s0>
</fA64>
<fA66 i1="01"><s0>USA</s0>
</fA66>
<fC01 i1="01" l="ENG"><s0>A technique for creating and searching a tree of patterns using relative  distances is presented.  The search is conducted to find patterns which are nearest neighbors of a given test pattern.  The structure of the tree is such that the search time is proportional to the distance between the test pattern and its nearest neighbor, which suggests the anomalous possibility that a larger tree, which can be expected on average to contain closer neighbors, can be searched faster than a smaller tree.  The technique has been used to recognize OCR digit samples derived from NIST data at an accuracy rate of 97% using a tree of 7,000 patterns.</s0>
</fC01>
<fC02 i1="01" i2="1"><s0>001D02C</s0>
</fC02>
<fC02 i1="02" i2="1"><s0>001D02A</s0>
</fC02>
<fC02 i1="03" i2="1"><s0>001D02B07B</s0>
</fC02>
<fC02 i1="04" i2="1"><s0>001A02I01</s0>
</fC02>
<fC03 i1="01" i2="1" l="ENG"><s0>Nearest neighbor</s0>
<s4>INC</s4>
</fC03>
<fC03 i1="02" i2="1" l="ENG"><s0>Distance metric</s0>
<s4>INC</s4>
</fC03>
<fC03 i1="03" i2="1" l="ENG"><s0>NIST digit samples</s0>
<s4>INC</s4>
</fC03>
<fC03 i1="04" i2="1" l="ENG"><s0>Pattern insertion</s0>
<s4>INC</s4>
</fC03>
<fC03 i1="05" i2="1" l="ENG"><s0>Pattern searching</s0>
<s4>INC</s4>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Application</s0>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Application</s0>
</fC03>
<fC03 i1="06" i2="X" l="GER"><s0>Anwendung</s0>
</fC03>
<fC03 i1="06" i2="X" l="SPA"><s0>Aplicación</s0>
</fC03>
<fC03 i1="07" i2="1" l="FRE"><s0>Reconnaissance optique caractère</s0>
</fC03>
<fC03 i1="07" i2="1" l="ENG"><s0>Optical character recognition</s0>
</fC03>
<fC03 i1="08" i2="1" l="FRE"><s0>Algorithme</s0>
</fC03>
<fC03 i1="08" i2="1" l="ENG"><s0>Algorithms</s0>
</fC03>
<fC03 i1="09" i2="1" l="FRE"><s0>Fonction récursive</s0>
</fC03>
<fC03 i1="09" i2="1" l="ENG"><s0>Recursive functions</s0>
</fC03>
<fC03 i1="10" i2="1" l="FRE"><s0>Structure donnée</s0>
</fC03>
<fC03 i1="10" i2="1" l="ENG"><s0>Data structures</s0>
</fC03>
<fC03 i1="11" i2="1" l="FRE"><s0>Calcul</s0>
</fC03>
<fC03 i1="11" i2="1" l="ENG"><s0>Calculations</s0>
</fC03>
<fC03 i1="12" i2="1" l="FRE"><s0>Reconnaissance forme</s0>
<s3>P</s3>
</fC03>
<fC03 i1="12" i2="1" l="ENG"><s0>Pattern recognition</s0>
<s3>P</s3>
</fC03>
<fC03 i1="13" i2="1" l="FRE"><s0>Théorie</s0>
</fC03>
<fC03 i1="13" i2="1" l="ENG"><s0>Theory</s0>
</fC03>
<fN21><s1>302</s1>
</fN21>
</pA>
</standard>
</inist>
</record>

Pour manipuler ce document sous Unix (Dilib)

EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/OcrV1/Data/PascalFrancis/Curation

HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000951 | SxmlIndent | more

HfdSelect -h $EXPLOR_AREA/Data/PascalFrancis/Curation/biblio.hfd -nk 000951 | SxmlIndent | more

Pour mettre un lien sur cette page dans le réseau Wicri

{{Explor lien
   |wiki=    Ticri/CIDE
   |area=    OcrV1
   |flux=    PascalFrancis
   |étape=   Curation
   |type=    RBID
   |clé=     Pascal:95-0527484
   |texte=   Search technique for pattern recognition using relative distances
}}

This area was generated with Dilib version V0.6.32.
Data generation: Sat Nov 11 16:53:45 2017. Site generation: Mon Mar 11 23:15:16 2024

	Serveur d'exploration sur l'OCR
	Attention, ce site est en cours de développement ! Attention, site généré par des moyens informatiques à partir de corpus bruts. Les informations ne sont donc pas validées.

Serveur d'exploration sur l'OCR

Search technique for pattern recognition using relative distances

Search technique for pattern recognition using relative distances

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri