Image Feature Extraction and Recognition of Abstractionism and Realism Style of Indonesian Paintings
This paper chooses and evaluates three feature vectors and their augmented feature vector for recognizing the styles of Indonesian paintings. The three feature extraction methods include the Gabor wavelet, histogram analysis, and number-of-edge analysis. The recognition purpose is to discriminate be...
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| creator | Tieta Antaresti, R P Arymurthy, A M |
| description | This paper chooses and evaluates three feature vectors and their augmented feature vector for recognizing the styles of Indonesian paintings. The three feature extraction methods include the Gabor wavelet, histogram analysis, and number-of-edge analysis. The recognition purpose is to discriminate between the abstractionism and the realism styles of Indonesian paintings. The experimental results using 115 painting images show that the use of number-of-edge features has given the best result with 66.23% accuracy. |
| doi_str_mv | 10.1109/ACT.2010.9 |
| format | Conference Proceeding |
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The three feature extraction methods include the Gabor wavelet, histogram analysis, and number-of-edge analysis. The recognition purpose is to discriminate between the abstractionism and the realism styles of Indonesian paintings. The experimental results using 115 painting images show that the use of number-of-edge features has given the best result with 66.23% accuracy.</description><identifier>ISBN: 9781424487462</identifier><identifier>ISBN: 1424487463</identifier><identifier>EISBN: 9780769542690</identifier><identifier>EISBN: 0769542697</identifier><identifier>DOI: 10.1109/ACT.2010.9</identifier><language>eng</language><publisher>IEEE</publisher><subject>Canny edge detection ; Feature extraction ; Gabor wavelet ; histogram ; Histograms ; Image edge detection ; Indonesian paintings ; Support vector machine classification ; Testing ; visual arts</subject><ispartof>2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies, 2010, p.149-152</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/5675821$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2051,27903,54897</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5675821$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Tieta Antaresti, R P</creatorcontrib><creatorcontrib>Arymurthy, A M</creatorcontrib><title>Image Feature Extraction and Recognition of Abstractionism and Realism Style of Indonesian Paintings</title><title>2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies</title><addtitle>act</addtitle><description>This paper chooses and evaluates three feature vectors and their augmented feature vector for recognizing the styles of Indonesian paintings. 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The experimental results using 115 painting images show that the use of number-of-edge features has given the best result with 66.23% accuracy.</description><subject>Canny edge detection</subject><subject>Feature extraction</subject><subject>Gabor wavelet</subject><subject>histogram</subject><subject>Histograms</subject><subject>Image edge detection</subject><subject>Indonesian paintings</subject><subject>Support vector machine classification</subject><subject>Testing</subject><subject>visual arts</subject><isbn>9781424487462</isbn><isbn>1424487463</isbn><isbn>9780769542690</isbn><isbn>0769542697</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1jE1Lw0AYhFdEUGouXr3kD6S--509ltBqoKDY3suavBtWko1kV7D_3rTWucw8zDCEPFBYUgrmaVXtlwxmMlckM7oErYwUTBm4PjMVTIhSC8VuSRbjJ8ySbGa4I2092A7zDdr0PWG-_kmTbZIfQ25Dm79jM3bBn3l0-eoj_tc-DpeF7U95l449njZ1aMeA0duQv1kfkg9dvCc3zvYRs4svyG6z3lcvxfb1ua5W28IbSIXWWApgTmrZMuAgkCtUzjFDQRqGSIW0bC45bzVyDrbkQkmnG0cta_mCPP69ekQ8fE1-sNPxIJWWJaP8F_suVW8</recordid><startdate>201012</startdate><enddate>201012</enddate><creator>Tieta Antaresti, R P</creator><creator>Arymurthy, A M</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201012</creationdate><title>Image Feature Extraction and Recognition of Abstractionism and Realism Style of Indonesian Paintings</title><author>Tieta Antaresti, R P ; Arymurthy, A M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-77e8402f575d20304e36e6ff2910592ee145a275d33d7e330a83465f7cf1a2d3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Canny edge detection</topic><topic>Feature extraction</topic><topic>Gabor wavelet</topic><topic>histogram</topic><topic>Histograms</topic><topic>Image edge detection</topic><topic>Indonesian paintings</topic><topic>Support vector machine classification</topic><topic>Testing</topic><topic>visual arts</topic><toplevel>online_resources</toplevel><creatorcontrib>Tieta Antaresti, R P</creatorcontrib><creatorcontrib>Arymurthy, A M</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>Tieta Antaresti, R P</au><au>Arymurthy, A M</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Image Feature Extraction and Recognition of Abstractionism and Realism Style of Indonesian Paintings</atitle><btitle>2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies</btitle><stitle>act</stitle><date>2010-12</date><risdate>2010</risdate><spage>149</spage><epage>152</epage><pages>149-152</pages><isbn>9781424487462</isbn><isbn>1424487463</isbn><eisbn>9780769542690</eisbn><eisbn>0769542697</eisbn><abstract>This paper chooses and evaluates three feature vectors and their augmented feature vector for recognizing the styles of Indonesian paintings. The three feature extraction methods include the Gabor wavelet, histogram analysis, and number-of-edge analysis. The recognition purpose is to discriminate between the abstractionism and the realism styles of Indonesian paintings. The experimental results using 115 painting images show that the use of number-of-edge features has given the best result with 66.23% accuracy.</abstract><pub>IEEE</pub><doi>10.1109/ACT.2010.9</doi><tpages>4</tpages></addata></record> |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Canny edge detection Feature extraction Gabor wavelet histogram Histograms Image edge detection Indonesian paintings Support vector machine classification Testing visual arts |
| title | Image Feature Extraction and Recognition of Abstractionism and Realism Style of Indonesian Paintings |
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