Close
Metadata

1. Identity statement
Reference TypeThesis or Dissertation (Thesis)
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier43zX63cXQZ5aVxUa/amcPJ
Repositoryime.usp.br/hirata/1997/09.02.16.38
Last Update2016:01.14.15.32.04 (UTC) administrator
Metadata Repositorydpi.inpe.br/banon/2001/02.23.19.30.12
Metadata Last Update2024:03.23.15.31.16 (UTC) administrator
Citation KeyHirataJr:1997:SeImMo
TitleSegmentação de Imagens por Morfologia Matemática
Alternate TitleImage segmentation by Mathematical Morphology
Short TitleSegmentação por MM
Year1997
Date1997-03
Access Date2024, May 05
Thesis TypeMasters Thesis
Secondary TypeTAE
Number of Files1
Size1887 KiB
2. Context
AuthorHirata Junior, Roberto
UniversityInstituto de Matemática e Estatística - USP
CitySão Paulo
History (UTC)2016-01-14 15:28:33 :: administrator -> banon ::
2016-01-14 15:32:05 :: banon -> administrator :: 1997
2016-01-14 15:42:16 :: administrator -> banon :: 1997
2016-01-14 16:21:37 :: banon -> administrator :: 1997
2016-01-14 16:23:18 :: administrator -> banon :: 1997
2016-01-14 16:23:34 :: banon -> administrator :: 1997
2016-01-14 17:07:12 :: administrator -> banon :: 1997
2016-01-14 17:24:06 :: banon -> administrator :: 1997
2020-07-11 22:42:09 :: administrator -> bibdigital :: 1997
2020-07-11 22:42:19 :: bibdigital -> administrator :: 1997
2024-03-23 15:31:16 :: administrator -> :: 1997
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsmathematical morphology
image segmentation
image analysis
fast algorithms
AbstractThis work shows what segmentation is and how to segment an image using Mathematical Morphology (\MM). It begins by introducing the subject segmentation by the classical approach and then by the morphological one. A short introduction to \MM is given and then two morphological approaches are given for segmentation: an heuristic and a non-heuristic one. The equivalence between the classical and the morphological approaches is shown and several illustrative examples of the morphological approach are given. The work also shows some important fast algorithms which simulate some of the operators used in the segmentations and how to use them to segment images. Finally it shows how to use the ideas behind the fast algorithms to implement efficiently the elementary operations and operators of \MM so other complex operators can be implemented more efficiently than before. Some experimental results are shown to verify this assumption.
AreaCOMP
ArrangementMM > Segmentação por MM
doc Directory Contentaccess
source Directory Content
tese.ps.gz 14/01/2016 15:24 2.0 MiB
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://urlib.net/ibi/43zX63cXQZ5aVxUa/amcPJ
zipped data URLhttp://urlib.net/zip/43zX63cXQZ5aVxUa/amcPJ
Languagept
Target Filevfinal.pdf
User Groupadministrator
banon
Visibilityshown
Read Permissionallow from all
Update Permissionnot transferred
5. Allied materials
Next Higher Units83LX3pFwXQZeBBx/cpksS
8JMKD3MGPCW/4AUUH9L
Citing Item Listsid.inpe.br/bibdigital/2024/03.23.15.30 1
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
NotesThis work has been supported by ProTeM-CC/CNPq through the AnIMoMat project, contract 680067/94-9.
Empty Fieldsacademicdepartment affiliation archivingpolicy archivist callnumber committee copyholder copyright course creatorhistory descriptionlevel dissemination doi e-mailaddress electronicmailaddress format group isbn issn label lineage mark mirrorrepository nextedition number numberofpages orcid parameterlist parentrepositories previousedition previouslowerunit progress readergroup resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark session sponsor subject tertiarymark tertiarytype url versiontype


Close