Plant Seed Image Recognition System (PSIRS)

The objective of this research is to develop a computer system, which can recognize a plant seed image. The system is called "Plant seed image recognition system (PSIRS)". The system consists of 5 processing modules, namely: 1) image acquisition, 2) image preprocessing, 3) feature extracti...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International Journal of Engineering and Technology 2011-12, Vol.3 (6), p.600-605
Hauptverfasser: Lurstwut, Benjamaporn, Pornpanomchai, Chomtip
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 605
container_issue 6
container_start_page 600
container_title International Journal of Engineering and Technology
container_volume 3
creator Lurstwut, Benjamaporn
Pornpanomchai, Chomtip
description The objective of this research is to develop a computer system, which can recognize a plant seed image. The system is called "Plant seed image recognition system (PSIRS)". The system consists of 5 processing modules, namely: 1) image acquisition, 2) image preprocessing, 3) feature extraction, 4) image recognition, and 5) display result. The experiment was conducted on more than 1,000 seed images by employing the Euclidean distance technique to recognize them. The precision rates of the system were 95.1 percent for correct matching in the training data set and 64.0 percent for unknown in the untrained data set. The average access time was 8.79 seconds per image.
doi_str_mv 10.7763/IJET.2011.V3.292
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1701093704</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1701093704</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1544-d998c5e7c6770618deed6872604cd009bde2d1844e8f2adb03686b55408628da3</originalsourceid><addsrcrecordid>eNqFkE1PwkAURSdGEwmyd9klxrS-N9-zNAS1hkRCke2kzAykhlLslAX_3hKMW1f3Lk5ubg4h9wiZUpI95e_TZUYBMVuxjBp6RQaoDEs15fz6rzN5S0YxfgEAMo5a4IA8znflvkuKEHyS1-U2JIvgmu2-6qpmnxSn2IU6Gc-LfFE83JGbTbmLYfSbQ_L5Ml1O3tLZx2s-eZ6lDgXnqTdGOxGUk0qBRO37bakVlcCdBzBrH6hHzXnQG1r6NTCp5VoIDlpS7Us2JOPL7qFtvo8hdrauogu7_mlojtGiAgTDFPD_UUHBUKVB9ChcUNc2MbZhYw9tVZftySLYs0V7tmjPFu2K2d4i-wHimGFw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1520927805</pqid></control><display><type>article</type><title>Plant Seed Image Recognition System (PSIRS)</title><source>EZB Electronic Journals Library</source><creator>Lurstwut, Benjamaporn ; Pornpanomchai, Chomtip</creator><creatorcontrib>Lurstwut, Benjamaporn ; Pornpanomchai, Chomtip</creatorcontrib><description>The objective of this research is to develop a computer system, which can recognize a plant seed image. The system is called "Plant seed image recognition system (PSIRS)". The system consists of 5 processing modules, namely: 1) image acquisition, 2) image preprocessing, 3) feature extraction, 4) image recognition, and 5) display result. The experiment was conducted on more than 1,000 seed images by employing the Euclidean distance technique to recognize them. The precision rates of the system were 95.1 percent for correct matching in the training data set and 64.0 percent for unknown in the untrained data set. The average access time was 8.79 seconds per image.</description><identifier>ISSN: 1793-8236</identifier><identifier>EISSN: 1793-8244</identifier><identifier>DOI: 10.7763/IJET.2011.V3.292</identifier><language>eng</language><subject>Access time ; Feature extraction ; Image acquisition ; Object recognition ; Preprocessing ; Recognition ; Seeds</subject><ispartof>International Journal of Engineering and Technology, 2011-12, Vol.3 (6), p.600-605</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c1544-d998c5e7c6770618deed6872604cd009bde2d1844e8f2adb03686b55408628da3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Lurstwut, Benjamaporn</creatorcontrib><creatorcontrib>Pornpanomchai, Chomtip</creatorcontrib><title>Plant Seed Image Recognition System (PSIRS)</title><title>International Journal of Engineering and Technology</title><description>The objective of this research is to develop a computer system, which can recognize a plant seed image. The system is called "Plant seed image recognition system (PSIRS)". The system consists of 5 processing modules, namely: 1) image acquisition, 2) image preprocessing, 3) feature extraction, 4) image recognition, and 5) display result. The experiment was conducted on more than 1,000 seed images by employing the Euclidean distance technique to recognize them. The precision rates of the system were 95.1 percent for correct matching in the training data set and 64.0 percent for unknown in the untrained data set. The average access time was 8.79 seconds per image.</description><subject>Access time</subject><subject>Feature extraction</subject><subject>Image acquisition</subject><subject>Object recognition</subject><subject>Preprocessing</subject><subject>Recognition</subject><subject>Seeds</subject><issn>1793-8236</issn><issn>1793-8244</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNqFkE1PwkAURSdGEwmyd9klxrS-N9-zNAS1hkRCke2kzAykhlLslAX_3hKMW1f3Lk5ubg4h9wiZUpI95e_TZUYBMVuxjBp6RQaoDEs15fz6rzN5S0YxfgEAMo5a4IA8znflvkuKEHyS1-U2JIvgmu2-6qpmnxSn2IU6Gc-LfFE83JGbTbmLYfSbQ_L5Ml1O3tLZx2s-eZ6lDgXnqTdGOxGUk0qBRO37bakVlcCdBzBrH6hHzXnQG1r6NTCp5VoIDlpS7Us2JOPL7qFtvo8hdrauogu7_mlojtGiAgTDFPD_UUHBUKVB9ChcUNc2MbZhYw9tVZftySLYs0V7tmjPFu2K2d4i-wHimGFw</recordid><startdate>20111201</startdate><enddate>20111201</enddate><creator>Lurstwut, Benjamaporn</creator><creator>Pornpanomchai, Chomtip</creator><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20111201</creationdate><title>Plant Seed Image Recognition System (PSIRS)</title><author>Lurstwut, Benjamaporn ; Pornpanomchai, Chomtip</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1544-d998c5e7c6770618deed6872604cd009bde2d1844e8f2adb03686b55408628da3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Access time</topic><topic>Feature extraction</topic><topic>Image acquisition</topic><topic>Object recognition</topic><topic>Preprocessing</topic><topic>Recognition</topic><topic>Seeds</topic><toplevel>online_resources</toplevel><creatorcontrib>Lurstwut, Benjamaporn</creatorcontrib><creatorcontrib>Pornpanomchai, Chomtip</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International Journal of Engineering and Technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lurstwut, Benjamaporn</au><au>Pornpanomchai, Chomtip</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Plant Seed Image Recognition System (PSIRS)</atitle><jtitle>International Journal of Engineering and Technology</jtitle><date>2011-12-01</date><risdate>2011</risdate><volume>3</volume><issue>6</issue><spage>600</spage><epage>605</epage><pages>600-605</pages><issn>1793-8236</issn><eissn>1793-8244</eissn><abstract>The objective of this research is to develop a computer system, which can recognize a plant seed image. The system is called "Plant seed image recognition system (PSIRS)". The system consists of 5 processing modules, namely: 1) image acquisition, 2) image preprocessing, 3) feature extraction, 4) image recognition, and 5) display result. The experiment was conducted on more than 1,000 seed images by employing the Euclidean distance technique to recognize them. The precision rates of the system were 95.1 percent for correct matching in the training data set and 64.0 percent for unknown in the untrained data set. The average access time was 8.79 seconds per image.</abstract><doi>10.7763/IJET.2011.V3.292</doi><tpages>6</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1793-8236
ispartof International Journal of Engineering and Technology, 2011-12, Vol.3 (6), p.600-605
issn 1793-8236
1793-8244
language eng
recordid cdi_proquest_miscellaneous_1701093704
source EZB Electronic Journals Library
subjects Access time
Feature extraction
Image acquisition
Object recognition
Preprocessing
Recognition
Seeds
title Plant Seed Image Recognition System (PSIRS)
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T09%3A35%3A14IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Plant%20Seed%20Image%20Recognition%20System%20(PSIRS)&rft.jtitle=International%20Journal%20of%20Engineering%20and%20Technology&rft.au=Lurstwut,%20Benjamaporn&rft.date=2011-12-01&rft.volume=3&rft.issue=6&rft.spage=600&rft.epage=605&rft.pages=600-605&rft.issn=1793-8236&rft.eissn=1793-8244&rft_id=info:doi/10.7763/IJET.2011.V3.292&rft_dat=%3Cproquest_cross%3E1701093704%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1520927805&rft_id=info:pmid/&rfr_iscdi=true