Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2007: administrator
Metadata Last Update2020: administrator
Citation KeyMontoya-ZegarraLeitTorr:2007:RoScSt
TitleRotation-Invariant and Scale-Invariant Steerable Pyramid Decomposition for Texture Image Retrieval
FormatPrinted, On-line.
Access Date2021, Jan. 25
Number of Files1
Size892 KiB
Context area
Author1 Montoya-Zegarra, Javier Alexander
2 Leite, Neucimar J.
3 Torres da Silva, Ricardo
Affiliation1 Institute of Computing, State University of Campinas
2 Institute of Computing, State University of Campinas
3 Institute of Computing, State University of Campinas
EditorFalcão, Alexandre Xavier
Lopes, Hélio Côrtes Vieira
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)
Conference LocationBelo Horizonte
DateOct. 7-10, 2007
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2007-07-20 21:19:24 :: -> administrator ::
2007-08-02 21:17:23 :: administrator -> ::
2008-07-17 14:09:42 :: -> administrator ::
2009-08-13 20:38:22 :: administrator -> banon ::
2010-08-28 20:02:27 :: banon -> administrator ::
2020-02-19 03:06:19 :: administrator -> :: 2007
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
KeywordsSteerable Pyramid Decomposition, Texture, Content-Based Image Retrieval, Texture-based Image Retrieval, Feature Extraction.
AbstractThis paper proposes a new rotation-invariant and scale-invariant representation for texture image retrieval based on Steerable Pyramid Decomposition. By calculating the mean and standard deviation of decomposed image subbands, the texture feature vectors are extracted. To obtain rotation or scale invariance, the feature elements are aligned by considering either the dominant orientation or dominant scale of the input textures. Experiments were conducted on the Brodatz database aiming to compare our approach to the conventional Steerable Pyramid Decomposition, and a recent proposal for texture characteriztion based on Gabor Wavelets with regard to their retrieval effectiveness. Results demonstrate the superiority of the proposed method in rotated and scaled image datasets.
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Target Filemontoya.zegarra-RotInvSclInvTexImgRet.pdf
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