Estimation of tip shape for carrot classification by machine vision
Identifieur interne : 003349 ( Main/Exploration ); précédent : 003348; suivant : 003350Estimation of tip shape for carrot classification by machine vision
Auteurs : M. S. Howarth [États-Unis] ; J. R. Brandon [États-Unis] ; S. W. Searcy [États-Unis] ; N. Kehtarnavaz [États-Unis]Source :
- Journal of Agricultural Engineering Research [ 0021-8634 ] ; 1992.
Abstract
Tip shape has been identified as an important carrot feature which is a major concern to both consumers and in post harvest operations. A classification method can help carrot breeders to measure the success of their breeding operations. Based on the Freeman chain code, a curvature profile was developed. Using a non-linear least squares technique known as the Marquardt method, the curvature profile was reduced to six parameters describing the carrot tip. These parameters were used to develop a Bayes decision function which classified carrot tips into five classes (sharp tapered to extremely blunt tips). This method was tested on 250 carrots. Of the 250 carrots tested, 14% were misclassified.
Url:
DOI: 10.1016/0021-8634(92)80078-7
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Istex, to step Corpus: 000599
- to stream Istex, to step Curation: 000591
- to stream Istex, to step Checkpoint: 002585
- to stream Main, to step Merge: 003530
- to stream Main, to step Curation: 003349
Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Estimation of tip shape for carrot classification by machine vision</title><author><name sortKey="Howarth, M S" sort="Howarth, M S" uniqKey="Howarth M" first="M. S." last="Howarth">M. S. Howarth</name></author><author><name sortKey="Brandon, J R" sort="Brandon, J R" uniqKey="Brandon J" first="J. R." last="Brandon">J. R. Brandon</name></author><author><name sortKey="Searcy, S W" sort="Searcy, S W" uniqKey="Searcy S" first="S. W." last="Searcy">S. W. Searcy</name></author><author><name sortKey="Kehtarnavaz, N" sort="Kehtarnavaz, N" uniqKey="Kehtarnavaz N" first="N." last="Kehtarnavaz">N. Kehtarnavaz</name></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:179C1422BD5D9ECD09EC7F9CB3B0CFACE19756AD</idno><date when="1992" year="1992">1992</date><idno type="doi">10.1016/0021-8634(92)80078-7</idno><idno type="url">https://api.istex.fr/document/179C1422BD5D9ECD09EC7F9CB3B0CFACE19756AD/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000599</idno><idno type="wicri:Area/Istex/Curation">000591</idno><idno type="wicri:Area/Istex/Checkpoint">002585</idno><idno type="wicri:doubleKey">0021-8634:1992:Howarth M:estimation:of:tip</idno><idno type="wicri:Area/Main/Merge">003530</idno><idno type="wicri:Area/Main/Curation">003349</idno><idno type="wicri:Area/Main/Exploration">003349</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Estimation of tip shape for carrot classification by machine vision</title><author><name sortKey="Howarth, M S" sort="Howarth, M S" uniqKey="Howarth M" first="M. S." last="Howarth">M. S. Howarth</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Agricultural Engineering, Texas, A & M University, College Station, TX 77843</wicri:regionArea><placeName><region type="state">Texas</region></placeName></affiliation></author><author><name sortKey="Brandon, J R" sort="Brandon, J R" uniqKey="Brandon J" first="J. R." last="Brandon">J. R. Brandon</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Agricultural Engineering, Texas, A & M University, College Station, TX 77843</wicri:regionArea><placeName><region type="state">Texas</region></placeName></affiliation></author><author><name sortKey="Searcy, S W" sort="Searcy, S W" uniqKey="Searcy S" first="S. W." last="Searcy">S. W. Searcy</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Agricultural Engineering, Texas, A & M University, College Station, TX 77843</wicri:regionArea><placeName><region type="state">Texas</region></placeName></affiliation></author><author><name sortKey="Kehtarnavaz, N" sort="Kehtarnavaz, N" uniqKey="Kehtarnavaz N" first="N." last="Kehtarnavaz">N. Kehtarnavaz</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Agricultural Engineering, Texas, A & M University, College Station, TX 77843</wicri:regionArea><placeName><region type="state">Texas</region></placeName></affiliation></author></analytic><monogr></monogr><series><title level="j">Journal of Agricultural Engineering Research</title><title level="j" type="abbrev">YJAER</title><idno type="ISSN">0021-8634</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1992">1992</date><biblScope unit="volume">53</biblScope><biblScope unit="supplement">C</biblScope><biblScope unit="page" from="123">123</biblScope><biblScope unit="page" to="139">139</biblScope></imprint><idno type="ISSN">0021-8634</idno></series><idno type="istex">179C1422BD5D9ECD09EC7F9CB3B0CFACE19756AD</idno><idno type="DOI">10.1016/0021-8634(92)80078-7</idno><idno type="PII">0021-8634(92)80078-7</idno><idno type="ArticleID">92800787</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0021-8634</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Tip shape has been identified as an important carrot feature which is a major concern to both consumers and in post harvest operations. A classification method can help carrot breeders to measure the success of their breeding operations. Based on the Freeman chain code, a curvature profile was developed. Using a non-linear least squares technique known as the Marquardt method, the curvature profile was reduced to six parameters describing the carrot tip. These parameters were used to develop a Bayes decision function which classified carrot tips into five classes (sharp tapered to extremely blunt tips). This method was tested on 250 carrots. Of the 250 carrots tested, 14% were misclassified.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Texas</li></region></list><tree><country name="États-Unis"><region name="Texas"><name sortKey="Howarth, M S" sort="Howarth, M S" uniqKey="Howarth M" first="M. S." last="Howarth">M. S. Howarth</name></region><name sortKey="Brandon, J R" sort="Brandon, J R" uniqKey="Brandon J" first="J. R." last="Brandon">J. R. Brandon</name><name sortKey="Kehtarnavaz, N" sort="Kehtarnavaz, N" uniqKey="Kehtarnavaz N" first="N." last="Kehtarnavaz">N. Kehtarnavaz</name><name sortKey="Searcy, S W" sort="Searcy, S W" uniqKey="Searcy S" first="S. W." last="Searcy">S. W. Searcy</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/OcrV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 003349 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 003349 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Ticri/CIDE
|area= OcrV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= ISTEX:179C1422BD5D9ECD09EC7F9CB3B0CFACE19756AD
|texte= Estimation of tip shape for carrot classification by machine vision
}}
| This area was generated with Dilib version V0.6.32. |  |