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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Repositorysid.inpe.br/sibgrapi@80/2007/08.01.20.23
Last Update2007:08.01.20.23.20 administrator
Metadatasid.inpe.br/sibgrapi@80/2007/08.01.20.23.21
Metadata Last Update2020:02.19.03.06.19 administrator
Citation KeyHofer:2007:HuIdBa
TitleDental Biometrics: Human Identification Based On Dental Work Information
FormatPrinted, On-line.
Year2007
DateOct. 7-10, 2007
Access Date2021, Jan. 19
Number of Files1
Size525 KiB
Context area
AuthorHofer, Michael
EditorFalcão, Alexandre Xavier
Lopes, Hélio Côrtes Vieira
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)
Conference LocationBelo Horizonte
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2007-08-01 20:23:21 :: m0399homi@fh-kaernten.at -> administrator ::
2007-08-02 21:17:50 :: administrator -> m0399homi@fh-kaernten.at ::
2008-07-17 14:09:43 :: m0399homi@fh-kaernten.at -> administrator ::
2009-08-13 20:38:29 :: administrator -> banon ::
2010-08-28 20:02:29 :: banon -> administrator ::
2020-02-19 03:06:19 :: administrator -> :: 2007
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Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsdental biometrics, biometrics, forensic odontology, dental radiograph, snake.
AbstractDental biometrics is used in forensic dentistry to identify or verify persons based on their dental radiographs. This paper presents a method for human identification based on dental work information. The proposed method works with three main processing steps: segmentation (feature extraction), creation of a dental code, and matching. In the segmentation step, seed points of the dental works are detected by thresholding. The final segmentation is obtained with a snake (active contour) algorithm. The dental code is defined from the position (upper or lower), the size of the dental works, and distance between neighboring dental works. The matching stage is performed with the Edit distance (Levenshtein distance). The costs for the insertion, deletion and substitution operations were adapted to make the matching algorithm more sensitive. The method was tested on a database including 68 dental radiographs and the results are encouraging.
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data URLhttp://urlib.net/rep/sid.inpe.br/sibgrapi@80/2007/08.01.20.23
zipped data URLhttp://urlib.net/zip/sid.inpe.br/sibgrapi@80/2007/08.01.20.23
Languageen
Target FileHofer-DentalBiometrics.pdf
User Groupm0399homi@fh-kaernten.at administrator
Visibilityshown
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Mirror Repositorydpi.inpe.br/banon-pc2@80/2006/08.30.19.27
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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Empty Fieldsaccessionnumber affiliation archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi e-mailaddress edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume

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