Journal article Open Access

Parameter selection for region-growing image segmentation algorithms using spatial autocorrelation

Espindola, Giovana; Camara, Gilberto; Reis, Ilka; Bins, Leonardo; Monteiro, Miguel


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="URL">https://zenodo.org/record/3831050</identifier>
  <creators>
    <creator>
      <creatorName>Espindola, Giovana</creatorName>
      <givenName>Giovana</givenName>
      <familyName>Espindola</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-2691-8496</nameIdentifier>
      <affiliation>Federal University of Piaui</affiliation>
    </creator>
    <creator>
      <creatorName>Camara, Gilberto</creatorName>
      <givenName>Gilberto</givenName>
      <familyName>Camara</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3681-487X</nameIdentifier>
      <affiliation>INPE (National Institute for Space Research), Brazil</affiliation>
    </creator>
    <creator>
      <creatorName>Reis, Ilka</creatorName>
      <givenName>Ilka</givenName>
      <familyName>Reis</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7199-8590</nameIdentifier>
      <affiliation>UFMG (Federal University of Minas Gerais)</affiliation>
    </creator>
    <creator>
      <creatorName>Bins, Leonardo</creatorName>
      <givenName>Leonardo</givenName>
      <familyName>Bins</familyName>
      <affiliation>INPE (National Institute for Space Research), Brazil</affiliation>
    </creator>
    <creator>
      <creatorName>Monteiro, Miguel</creatorName>
      <givenName>Miguel</givenName>
      <familyName>Monteiro</familyName>
      <affiliation>INPE (National Institute for Space Research), Brazil</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Parameter selection for region-growing image segmentation algorithms using spatial autocorrelation</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2006</publicationYear>
  <subjects>
    <subject>Image Segmentation, Spatial Autocorrelation</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2006-02-06</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3831050</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1080/01431160600617194</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Region‐growing segmentation algorithms are useful for remote sensing image segmentation. These algorithms need the user to supply control parameters, which control the quality of the resulting segmentation. An objective function is proposed for selecting suitable parameters for region‐growing algorithms to ensure best quality results. It considers that a segmentation has two desirable properties: each of the resulting segments should be internally homogeneous and should be distinguishable from its neighbourhood. The measure combines a spatial autocorrelation indicator that detects separability between regions and a variance indicator that expresses the overall homogeneity of the regions.eng&lt;/p&gt;</description>
  </descriptions>
</resource>
10
29
views
downloads
Views 10
Downloads 29
Data volume 10.6 MB
Unique views 9
Unique downloads 22

Share

Cite as