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Reference TypeConference Paper (Conference Proceedings)
Last Update2017: administrator
Metadata Last Update2020: administrator
Citation KeyMattosFerSilRivBra:2017:AsTeDe
TitleAssessing Texture Descriptors for Seismic Image Retrieval
DateOct. 17-20, 2017
Access Date2021, Jan. 21
Number of Files1
Size575 KiB
Context area
Author1 Mattos, Andrea Britto
2 Ferreira, Rodrigo S.
3 Silva, Reinaldo M. da Gama e
4 Riva, Mateus
5 Brazil, Emilio Vital
Affiliation1 IBM Research
2 IBM Research
3 IBM Research
5 IBM Research
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylène
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, João Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2017-08-22 12:58:02 :: -> administrator ::
2020-02-19 02:01:42 :: administrator -> :: 2017
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
Keywordsimage retrieval, seismic.
AbstractMuch work has been done on the assessment of texture descriptors for image retrieval in many domains. In this work, we evaluate the accuracy and performance of three well-known texture descriptors -- Gabor Filters, GLCM, and LBP -- for seismic image retrieval. These subsurface images pose challenges yet not thoroughly investigated in previous works, which are addressed and evaluated in our experiments. We asked for domain experts to annotate two seismic cubes, Penobscot 3D and Netherlands F3, and used them to evaluate texture descriptors, corresponding parameters, and similarity metrics with the potential to retrieve visually similar regions of the considered datasets. While GLCM is used in the vast majority of works in this area, our findings indicate that LBP has the potential to produce satisfying results with lower computational cost.
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Next Higher Units8JMKD3MGPAW/3PJT9LS
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