Green image segmentation analysis of Google Earth image to rank world universities using PHP and MATLAB
University ranking systems are some effort to list universities worldwide in to an order based on some predetermined parameters. The percentage of the green area in each university that is captured by satellite can be used as a world university ranking parameter. In this work, green images taken fro...
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| creator | Sari, R. F. Sulaiman, M. Fajar, M. N. |
| description | University ranking systems are some effort to list universities worldwide in to an order based on some predetermined parameters. The percentage of the green area in each university that is captured by satellite can be used as a world university ranking parameter. In this work, green images taken from Google Earth have been processed through a segmentation stage using hsv threshold method. Images from 200 university from various countries on five continents have been analyzed, after segmentation process. University satellite images are taken from Google Earth and 75% of them are captured in 2009 and 2010. The result shows that hsv thresholding method is 21% better than global thresholding method and 59% better than local thresholding method. On execution time analysis, web processing takes 19.5% longer than the processing that is done without web interface. |
| doi_str_mv | 10.1109/TENCON.2011.6129296 |
| format | Conference Proceeding |
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F. ; Sulaiman, M. ; Fajar, M. N.</creator><creatorcontrib>Sari, R. F. ; Sulaiman, M. ; Fajar, M. N.</creatorcontrib><description>University ranking systems are some effort to list universities worldwide in to an order based on some predetermined parameters. The percentage of the green area in each university that is captured by satellite can be used as a world university ranking parameter. In this work, green images taken from Google Earth have been processed through a segmentation stage using hsv threshold method. Images from 200 university from various countries on five continents have been analyzed, after segmentation process. University satellite images are taken from Google Earth and 75% of them are captured in 2009 and 2010. The result shows that hsv thresholding method is 21% better than global thresholding method and 59% better than local thresholding method. 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The result shows that hsv thresholding method is 21% better than global thresholding method and 59% better than local thresholding method. On execution time analysis, web processing takes 19.5% longer than the processing that is done without web interface.</description><subject>Earth</subject><subject>Educational institutions</subject><subject>Google</subject><subject>Google Earth</subject><subject>Green Campus</subject><subject>Green products</subject><subject>Image color analysis</subject><subject>Image Processing</subject><subject>Image segmentation</subject><subject>MATLAB</subject><subject>University Ranking</subject><issn>2159-3442</issn><issn>2159-3450</issn><isbn>9781457702563</isbn><isbn>1457702568</isbn><isbn>9781457702556</isbn><isbn>145770255X</isbn><isbn>9781457702549</isbn><isbn>1457702541</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVUM1OAjEYrH-JBHkCLn2BxX7t9u-IBMEEgQOeSdn9dq0uXdOuGt7eTSQmzmUymclkMoSMgU0AmL3fzdezzXrCGcBEAbfcqgsystpALrVmXEp1SQYcpM1ELtnVP0-J6z8v57dklNIb66GYyYENSL2IiIH6o6uRJqyPGDrX-TZQF1xzSj7RtqKLtq0bpHMXu9dztmtpdOGdfrexKeln8F8Yk-88JvqZfKjpdrntO0r6PN2tpg935KZyTcLRmYfk5XG-my2z1WbxNJuuMg9adpmRmh-cKoxymHMsRV5pW9qD62XFKnMwSupCMBBaaVtpMBoKp7QrOJcCnBiS8W-vR8T9R-zHxtP-fJv4ARihXIk</recordid><startdate>201111</startdate><enddate>201111</enddate><creator>Sari, R. 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N.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Sari, R. F.</au><au>Sulaiman, M.</au><au>Fajar, M. N.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Green image segmentation analysis of Google Earth image to rank world universities using PHP and MATLAB</atitle><btitle>TENCON 2011 - 2011 IEEE Region 10 Conference</btitle><stitle>TENCON</stitle><date>2011-11</date><risdate>2011</risdate><spage>1170</spage><epage>1174</epage><pages>1170-1174</pages><issn>2159-3442</issn><eissn>2159-3450</eissn><isbn>9781457702563</isbn><isbn>1457702568</isbn><eisbn>9781457702556</eisbn><eisbn>145770255X</eisbn><eisbn>9781457702549</eisbn><eisbn>1457702541</eisbn><abstract>University ranking systems are some effort to list universities worldwide in to an order based on some predetermined parameters. The percentage of the green area in each university that is captured by satellite can be used as a world university ranking parameter. In this work, green images taken from Google Earth have been processed through a segmentation stage using hsv threshold method. Images from 200 university from various countries on five continents have been analyzed, after segmentation process. University satellite images are taken from Google Earth and 75% of them are captured in 2009 and 2010. The result shows that hsv thresholding method is 21% better than global thresholding method and 59% better than local thresholding method. On execution time analysis, web processing takes 19.5% longer than the processing that is done without web interface.</abstract><pub>IEEE</pub><doi>10.1109/TENCON.2011.6129296</doi><tpages>5</tpages></addata></record> |
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| identifier | ISSN: 2159-3442 |
| ispartof | TENCON 2011 - 2011 IEEE Region 10 Conference, 2011, p.1170-1174 |
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| language | eng |
| recordid | cdi_ieee_primary_6129296 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Earth Educational institutions Google Earth Green Campus Green products Image color analysis Image Processing Image segmentation MATLAB University Ranking |
| title | Green image segmentation analysis of Google Earth image to rank world universities using PHP and MATLAB |
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