%0 Journal Article
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%@nexthigherunit 8JMKD3MGPCW/3ESGTTP
%@resumeid
%@resumeid 8JMKD3MGP5W/3E3JEJL
%X This work proposes a general image classification method, based in possibility theory and clustering. We illustrate our approach with a CBERS image and compare the results obtained by applying our method to other classification methods.
%T A clustering-based possibilistic method for image classification
%@electronicmailaddress isabela@lac.inpe.br
%@electronicmailaddress sandra@lac.inpe.br
%K image classification, clustering, possibility theory, similarity relation.
%@secondarytype PRE PI
%@archivingpolicy denypublisher denyfinaldraft12
%@usergroup administrator
%@usergroup banon
%@usergroup marciana
%@usergroup sergio
%@group LAC-INPE-MCT-BR
%@group LAC-INPE-MCT-BR
%3 a clustering-based, drummond, isabela.pdf
%@copyholder SID/SCD
%@secondarykey INPE-15130-PRE/10037
%@issn 0302-9743
%2 sid.inpe.br/iris@1916/2005/08.23.12.41.54
%@affiliation Instituto Nacional de Pesquisas Espaciais, Laboratório Associado de Computação e Matemática  Aplicada, (INPE, LAC)
%B Lecture Notes in Computer Science
%@versiontype publisher
%P 454-463
%4 sid.inpe.br/iris@1916/2005/08.23.12.41
%@documentstage not transferred
%D 2004
%V 3171
%A Drummond,  Isabela Neves,
%A Sandri, Sandra Aparecida,
%@dissemination WEBSCI; PORTALCAPES; COMPENDEX.
%@area COMP