<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Conference Proceedings">
		<site>mtc-m16c.sid.inpe.br 804</site>
		<holdercode>{isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}</holdercode>
		<identifier>8JMKD3MGPDW34P/3KP38AL</identifier>
		<repository>sid.inpe.br/mtc-m16c/2015/12.10.18.21</repository>
		<lastupdate>2016:02.23.13.20.41 sid.inpe.br/mtc-m18@80/2008/03.17.15.17 simone</lastupdate>
		<metadatarepository>sid.inpe.br/mtc-m16c/2015/12.10.18.21.44</metadatarepository>
		<metadatalastupdate>2023:01.30.13.10.11 sid.inpe.br/mtc-m18@80/2008/03.17.15.17 administrator {D 2015}</metadatalastupdate>
		<issn>2179-4820</issn>
		<citationkey>SoaresKörtFons:2015:ImDiSe</citationkey>
		<title>Improvements of the divide and segment method for parallel image segmentation</title>
		<format>CD-ROM, On-line.</format>
		<year>2015</year>
		<secondarytype>PRE CN</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>1056 KiB</size>
		<author>Soares, Anderson Reis,</author>
		<author>Körting, Thales Sehn,</author>
		<author>Fonseca, Leila M. Garcia,</author>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<editor>Fileto, Renato,</editor>
		<editor>Korting, Thales Sehn,</editor>
		<e-mailaddress>lubia@dpi.inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Geoinformática, 16 (GEOINFO)</conferencename>
		<conferencelocation>Campos do Jordão</conferencelocation>
		<date>27 nov. a 02 dez. 2015</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>222-232</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>Full papers</tertiarytype>
		<transferableflag>1</transferableflag>
		<abstract>Remote Sensing is an important source of information about the dynamics of Earth's land and oceans, but retrieve information from this technique, is a challenge.  Segmentation is a traditional method in remote sensing, which have a high computational cost. An alternative to suppress this problem is use parallel approaches, which split the image into tiles, and segment each one individually. However, the divisions among tiles are not natural, which create inconsistent objects. In this work, we extended our previous work, which used non-crisp borders computed based on graph-theory. By applying this non-crisp line cut, we avoid the post-processing of neighboring regions, and therefore speed up the segmentation.</abstract>
		<area>SRE</area>
		<language>en</language>
		<targetfile>soares2015improvements.pdf</targetfile>
		<usergroup>lubia@dpi.inpe.br</usergroup>
		<usergroup>simone</usergroup>
		<visibility>shown</visibility>
		<documentstage>not transferred</documentstage>
		<mirrorrepository>dpi.inpe.br/banon-pc2@80/2006/07.04.20.21</mirrorrepository>
		<nexthigherunit>8JMKD3MGPDW34P/42T288P</nexthigherunit>
		<nexthigherunit>8JMKD3MGPDW34P/48F29JE</nexthigherunit>
		<citingitemlist>sid.inpe.br/mtc-m16c/2020/07.21.21.26 3</citingitemlist>
		<hostcollection>sid.inpe.br/mtc-m18@80/2008/03.17.15.17</hostcollection>
		<username>simone</username>
		<lasthostcollection>sid.inpe.br/mtc-m18@80/2008/03.17.15.17</lasthostcollection>
		<url>http://mtc-m16c.sid.inpe.br/rep-/sid.inpe.br/mtc-m16c/2015/12.10.18.21</url>
	</metadata>
</metadatalist>