Feature extractor for the classification of approved Halal logo in Malaysia

Feature extractor for the classification of approved Halal logo in Malaysia

This paper present a new feature extractors called the Fractionalized Principle Magnitude (FPM) that is evaluated in the classification of approved Halal logo with respect to classification accuracy and time consumptions. Feature can be classified into two group; global feature and local feature. In...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Saipullah, K. M., Ismail, N. A., Soo, Y.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Feature Extractor
Fourier Principle Magnitude
logo classification
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 500
container_issue
container_start_page 495
container_title
container_volume
creator Saipullah, K. M.
Ismail, N. A.
Soo, Y.
description This paper present a new feature extractors called the Fractionalized Principle Magnitude (FPM) that is evaluated in the classification of approved Halal logo with respect to classification accuracy and time consumptions. Feature can be classified into two group; global feature and local feature. In this study, several feature extractors have been compared with the proposed method such as histogram of gradient (HOG), Hu moment, Zernike moment and wavelet co-occurrence histogram (WCH). The experiments are conducted on 50 different approved Halal logos. The result shows that proposed FPM method achieves the highest accuracy with 90.4% whereas HOG, Zernike moment, WCH and Hu moment achieve 75.2%, 64.4%, 47.2% 44.4% of accuracies, respectively.
doi_str_mv 10.1109/ICCSCE.2012.6487196
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6487196</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6487196</ieee_id><sourcerecordid>6487196</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-4103cc163791d374e5f9747e1abe97f35e1f4c68f577d6b6a33c2a834c3cb6093</originalsourceid><addsrcrecordid>eNo1j81Kw0AUhUdEUGueoJt5gcS5mb_MUkJrixUX6rrcTO7oSGxCMop9ewPWxeHwLb4Dh7EliAJAuNttXT_Xq6IUUBZGVRacOWPXoIyVEhSoc5Y5W_1zqS9ZNk0fQojZNpXQV-xhTZi-RuL0k0b0qR95mJPeifsOpymG6DHF_sD7wHEYxv6bWr7BDjve9W89jwf-ONNxinjDLgJ2E2WnXrDX9eql3uS7p_ttfbfLI1idcgVCeg9GWgettIp0cFZZAmzI2SA1QVDeVEFb25rGoJS-xEoqL31jhJMLtvzbjUS0H8b4ieNxf_ovfwEMqk6W</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Feature extractor for the classification of approved Halal logo in Malaysia</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Saipullah, K. M. ; Ismail, N. A. ; Soo, Y.</creator><creatorcontrib>Saipullah, K. M. ; Ismail, N. A. ; Soo, Y.</creatorcontrib><description>This paper present a new feature extractors called the Fractionalized Principle Magnitude (FPM) that is evaluated in the classification of approved Halal logo with respect to classification accuracy and time consumptions. Feature can be classified into two group; global feature and local feature. In this study, several feature extractors have been compared with the proposed method such as histogram of gradient (HOG), Hu moment, Zernike moment and wavelet co-occurrence histogram (WCH). The experiments are conducted on 50 different approved Halal logos. The result shows that proposed FPM method achieves the highest accuracy with 90.4% whereas HOG, Zernike moment, WCH and Hu moment achieve 75.2%, 64.4%, 47.2% 44.4% of accuracies, respectively.</description><identifier>ISBN: 9781467331425</identifier><identifier>ISBN: 1467331422</identifier><identifier>EISBN: 1467331414</identifier><identifier>EISBN: 1467331430</identifier><identifier>EISBN: 9781467331432</identifier><identifier>EISBN: 9781467331418</identifier><identifier>DOI: 10.1109/ICCSCE.2012.6487196</identifier><language>eng</language><publisher>IEEE</publisher><subject>Feature Extractor ; Fourier Principle Magnitude ; logo classification</subject><ispartof>2012 IEEE International Conference on Control System, Computing and Engineering, 2012, p.495-500</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6487196$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2057,27924,54919</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6487196$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Saipullah, K. M.</creatorcontrib><creatorcontrib>Ismail, N. A.</creatorcontrib><creatorcontrib>Soo, Y.</creatorcontrib><title>Feature extractor for the classification of approved Halal logo in Malaysia</title><title>2012 IEEE International Conference on Control System, Computing and Engineering</title><addtitle>ICCSCE</addtitle><description>This paper present a new feature extractors called the Fractionalized Principle Magnitude (FPM) that is evaluated in the classification of approved Halal logo with respect to classification accuracy and time consumptions. Feature can be classified into two group; global feature and local feature. In this study, several feature extractors have been compared with the proposed method such as histogram of gradient (HOG), Hu moment, Zernike moment and wavelet co-occurrence histogram (WCH). The experiments are conducted on 50 different approved Halal logos. The result shows that proposed FPM method achieves the highest accuracy with 90.4% whereas HOG, Zernike moment, WCH and Hu moment achieve 75.2%, 64.4%, 47.2% 44.4% of accuracies, respectively.</description><subject>Feature Extractor</subject><subject>Fourier Principle Magnitude</subject><subject>logo classification</subject><isbn>9781467331425</isbn><isbn>1467331422</isbn><isbn>1467331414</isbn><isbn>1467331430</isbn><isbn>9781467331432</isbn><isbn>9781467331418</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1j81Kw0AUhUdEUGueoJt5gcS5mb_MUkJrixUX6rrcTO7oSGxCMop9ewPWxeHwLb4Dh7EliAJAuNttXT_Xq6IUUBZGVRacOWPXoIyVEhSoc5Y5W_1zqS9ZNk0fQojZNpXQV-xhTZi-RuL0k0b0qR95mJPeifsOpymG6DHF_sD7wHEYxv6bWr7BDjve9W89jwf-ONNxinjDLgJ2E2WnXrDX9eql3uS7p_ttfbfLI1idcgVCeg9GWgettIp0cFZZAmzI2SA1QVDeVEFb25rGoJS-xEoqL31jhJMLtvzbjUS0H8b4ieNxf_ovfwEMqk6W</recordid><startdate>201211</startdate><enddate>201211</enddate><creator>Saipullah, K. M.</creator><creator>Ismail, N. A.</creator><creator>Soo, Y.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201211</creationdate><title>Feature extractor for the classification of approved Halal logo in Malaysia</title><author>Saipullah, K. M. ; Ismail, N. A. ; Soo, Y.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-4103cc163791d374e5f9747e1abe97f35e1f4c68f577d6b6a33c2a834c3cb6093</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Feature Extractor</topic><topic>Fourier Principle Magnitude</topic><topic>logo classification</topic><toplevel>online_resources</toplevel><creatorcontrib>Saipullah, K. M.</creatorcontrib><creatorcontrib>Ismail, N. A.</creatorcontrib><creatorcontrib>Soo, Y.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Saipullah, K. M.</au><au>Ismail, N. A.</au><au>Soo, Y.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Feature extractor for the classification of approved Halal logo in Malaysia</atitle><btitle>2012 IEEE International Conference on Control System, Computing and Engineering</btitle><stitle>ICCSCE</stitle><date>2012-11</date><risdate>2012</risdate><spage>495</spage><epage>500</epage><pages>495-500</pages><isbn>9781467331425</isbn><isbn>1467331422</isbn><eisbn>1467331414</eisbn><eisbn>1467331430</eisbn><eisbn>9781467331432</eisbn><eisbn>9781467331418</eisbn><abstract>This paper present a new feature extractors called the Fractionalized Principle Magnitude (FPM) that is evaluated in the classification of approved Halal logo with respect to classification accuracy and time consumptions. Feature can be classified into two group; global feature and local feature. In this study, several feature extractors have been compared with the proposed method such as histogram of gradient (HOG), Hu moment, Zernike moment and wavelet co-occurrence histogram (WCH). The experiments are conducted on 50 different approved Halal logos. The result shows that proposed FPM method achieves the highest accuracy with 90.4% whereas HOG, Zernike moment, WCH and Hu moment achieve 75.2%, 64.4%, 47.2% 44.4% of accuracies, respectively.</abstract><pub>IEEE</pub><doi>10.1109/ICCSCE.2012.6487196</doi><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 9781467331425
ispartof 2012 IEEE International Conference on Control System, Computing and Engineering, 2012, p.495-500
issn
language eng
recordid cdi_ieee_primary_6487196
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Feature Extractor
Fourier Principle Magnitude
logo classification
title Feature extractor for the classification of approved Halal logo in Malaysia
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T08%3A34%3A25IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Feature%20extractor%20for%20the%20classification%20of%20approved%20Halal%20logo%20in%20Malaysia&rft.btitle=2012%20IEEE%20International%20Conference%20on%20Control%20System,%20Computing%20and%20Engineering&rft.au=Saipullah,%20K.%20M.&rft.date=2012-11&rft.spage=495&rft.epage=500&rft.pages=495-500&rft.isbn=9781467331425&rft.isbn_list=1467331422&rft_id=info:doi/10.1109/ICCSCE.2012.6487196&rft_dat=%3Cieee_6IE%3E6487196%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1467331414&rft.eisbn_list=1467331430&rft.eisbn_list=9781467331432&rft.eisbn_list=9781467331418&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6487196&rfr_iscdi=true